Empty shelves or lost keys? Recall is the bottleneck for parametric factuality
Generative AI
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The Truth Stays in the Family: Enhancing Contextual Grounding via Inherited Truthful Heads in Model Lineages
arXiv:2606.15821v2 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have produced many specialized multimodal LLMs (MLLMs) that share common foundational LLMs, forming distinct…
CurveFP: Rational-Radix Logarithmic Datatypes with Closed Products for Language Models
arXiv:2608.10010v1 Announce Type: new Abstract: Low-precision datatypes reduce language-model cost, but most formats optimize scalar fidelity while leaving the arithmetic induced by their products unchanged. We…
A Quantum Roadmap for Softmax Attention: Exact Born-Rule Analogs for Softmax Attention on the Probability Simplex
arXiv:2608.11173v1 Announce Type: cross Abstract: The attention mechanism forms the foundation of many modern AI models such as the Transformer. In one subclass of problems where attention is used, inputs and outputs…
Beyond Fixed Luminance: Towards Panchromatic and Orthochromatic Image Colorization
arXiv:2608.10798v1 Announce Type: cross Abstract: Most image colorization systems operate in $Lab$ space by predicting chroma ($ab$) while preserving an input-derived luminance channel ($L$). While effective on standard…
Post-Calibration Reliability Reranking of Relevance Decisions via Label-wise Monotone Projection
arXiv:2608.10406v1 Announce Type: cross Abstract: Web search, product search, and question-answering retrieval systems often assign a relevance label and confidence score to each query-candidate pair. The relevance…
Nonlinear multi-study sparse factor analysis
arXiv:2601.18128v2 Announce Type: replace-cross Abstract: High-dimensional data often exhibit variation that can be captured by lower-dimensional factors. For high-dimensional data from multiple studies, one goal is to…
Null-Space Flow Matching for MIMO Channel Estimation in Latency-Constrained Systems
arXiv:2604.22005v2 Announce Type: replace-cross Abstract: Accurate yet low-latency channel state information (CSI) acquisition is essential for multiple-input multiple-output (MIMO) communication systems. While advanced…
Causal Variational Deep Embedding: A Family of Interventional Generators for Confounded Images
arXiv:2606.21806v2 Announce Type: replace Abstract: Deep generative models reproduce the observational distribution of their training data, inheriting any spurious associations it contains. A common source is an…
Coordinating the Unknown Lipschitz Constant in Multiplayer Bandits
arXiv:2608.10526v1 Announce Type: new Abstract: Motivated by decentralized applications, we study cooperative multi-agent bandits in continuous (Lipschitz) action spaces when the Lipschitz constant is unknown. We…
Mapping and Measuring the Behavioral Evolution of Large Language Models
arXiv:2608.11027v1 Announce Type: new Abstract: Benchmark leaderboards summarize how well a language model performs, but not how its behavior relates to that of other models or changes across generations. We…
MT-PingEval: Evaluating Multi-Turn Collaboration with Private Information Games
arXiv:2602.24188v2 Announce Type: replace-cross Abstract: We present a scalable and verifiable methodology for evaluating language models in multi-turn interactions, using a suite of collaborative games that require…
Progressive Semantic Communication for Efficient Edge-Cloud Vision-Language Models
arXiv:2604.26508v2 Announce Type: replace Abstract: Deploying Vision-Language Models (VLMs) on edge devices remains challenging due to their substantial computational and memory demands, which exceed the capabilities of…
Coachable agents for interactive gameplay
arXiv:2607.00642v2 Announce Type: replace-cross Abstract: Reinforcement learning has proven to be a valuable tool in the creation of advanced AI and robotic systems, contributing to everything from game playing to…
SearchArt: Training Long-Horizon Search Agent with Scalable Synthetic and Verified Task
arXiv:2607.24850v2 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have enabled search agents to autonomously tackle complex tasks across extended search and reasoning horizons.…
Learning Disease-Sensitive Latent Interaction Graphs From Noisy Cardiac Flow Measurements
arXiv:2602.23035v2 Announce Type: replace Abstract: Cardiac blood flow patterns contain rich information about disease severity and clinical interventions, yet current imaging and computational methods fail to capture…
Learning in ImaginationLand: Omnidirectional Policies through 3D Generative Models (OP-Gen)
arXiv:2509.06191v2 Announce Type: replace-cross Abstract: Recent 3D generative models, which are capable of generating full object shapes from just a few images, now open up new opportunities in robotics. In this work,…
MultiModal Code-Switching: Interleaving Visual Objects into Language for Explicit Object-Level Alignment
arXiv:2608.11167v1 Announce Type: cross Abstract: Existing Multimodal Large Language Models (MLLMs) predominantly rely on image-text pairs for modality alignment pretraining, mapping global image representations to long…
Efficient Hypergradient Descent for Inverse Reinforcement Learning
arXiv:2608.11052v1 Announce Type: new Abstract: Inverse reinforcement learning (IRL) aims to recover a reward function under which the resulting policy reproduces the behavior observed in expert demonstrations. A…
Sheaf-Based Federated Representation Learning
arXiv:2608.10016v1 Announce Type: new Abstract: Heterogeneous federated systems require agents to learn and exchange informative representations despite differences in data distributions, sensing modalities, model…
Diffract: Spectral View of LLM Domain Adaptation
arXiv:2608.10850v1 Announce Type: new Abstract: We study continual pre-training (CPT) as a mechanism for adapting general-purpose large language models to specialized domains: mathematics, instruction, code, and natural…
LLMs Encode Their Failures: Predicting Success from Pre-Generation Activations
arXiv:2602.09924v4 Announce Type: replace-cross Abstract: Running LLMs with extended reasoning on every problem is expensive, but determining which inputs actually require additional compute remains challenging. We…
Iterative Erasure Count Is Not an Affine-Invariant Concept Dimension
arXiv:2608.10566v1 Announce Type: cross Abstract: How many directions does a neural representation use to encode a concept? A common answer repeatedly erases probe directions and reports the stopping count or cumulative…
The Kuramoto Neural Operator: Learning to Solve PDEs via Coupled Oscillator Dynamics
arXiv:2608.10234v1 Announce Type: cross Abstract: Operator learning is a rapidly advancing area of computational science. It is particularly well suited to problems where a partial differential equation (PDE) must be…
TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting
arXiv:2511.18539v3 Announce Type: replace Abstract: We propose TimePre, a simple framework that unifies the efficiency of Multilayer Perceptron (MLP)-based models with the distributional flexibility of Multiple Choice…
Retrieval-Corrected Conformal Prediction for Time Series
arXiv:2608.10553v1 Announce Type: new Abstract: Conformal prediction (CP) provides distribution-free prediction intervals for fixed forecasters, but its standard calibration procedure is often inefficient for time…
Projected climate memory and inherited warm-tail risk in accelerated European summer warming
arXiv:2608.09966v1 Announce Type: cross Abstract: European summer warming reflects interactions among background change, persistent ocean--land--circulation states, and same-season variability. We develop an empirical…
Forecasting With LLMs: Improved Generalization Through Feature Steering
arXiv:2606.27199v2 Announce Type: replace-cross Abstract: Successful forecasting involves identifying patterns between historical and future states of the world which generalize to future observations. We apply LLMs to…
Discrete Coefficients and Open Invariant Covers in the Homology of Ample Groupoids
arXiv:2603.20861v2 Announce Type: replace-cross Abstract: The homology of an ample groupoid is computed from the complex of compactly supported continuous functions on the nerve. Two hypotheses routinely imposed on this…
Putting a Face to Forgetting: Continual Learning meets Mechanistic Interpretability
arXiv:2601.22012v3 Announce Type: replace Abstract: Catastrophic forgetting in continual learning is often measured at the performance or last-layer representation level, overlooking the underlying mechanisms. We…
Bayesian Symbolic Regression with Entropic Reinforcement Learning
arXiv:2608.09617v2 Announce Type: replace Abstract: Symbolic regression is the problem of finding an algebraic expression describing a stochastic dependence of a target variable on a set of inputs. Unlike forms of…
Masked Neural Detection for Run-Length-Limited Channel Coding in Molecular Communication
arXiv:2606.12489v2 Announce Type: replace-cross Abstract: Molecular communication (MC) suffers from severe diffusion memory because molecules released for one symbol may arrive during later symbol intervals. Neural…
The Exact Replica Threshold for Nonlinear Moments of Quantum States
arXiv:2604.22627v2 Announce Type: replace-cross Abstract: Joint measurements on multiple copies of a quantum state provide access to nonlinear observables such as $\operatorname{tr}(\rho^t)$, but whether replica number…
STCAD: Scalable Trajectory Clustering and Anomaly Detection on Terabyte-Scale AIS Data
arXiv:2608.10249v1 Announce Type: new Abstract: We present a scalable framework for unsupervised clustering of maritime trajectories derived from terabyte-scale Automatic Identification System (AIS) archives.…
Time-Series Foundation Model Embeddings for Remaining Useful Life Estimation
arXiv:2606.11990v3 Announce Type: replace Abstract: Remaining Useful Life (RUL) prediction is essential for industrial predictive maintenance, yet many learning-based approaches rely on extensive feature engineering or…
Rule of Thumb: Explaining Artificial Intelligence Systems using Partial Information
arXiv:2608.10766v1 Announce Type: cross Abstract: Explainable Artificial Intelligence (XAI) seeks to explain how an Artificial Intelligence (AI) system arrived at a particular decision. We propose ''Rule of Thumb''…
Automatic Field-of-View Adjustment for a View-Expansive Microscope via LSTM-Based Gaze and Pipette Motion Interpretation
arXiv:2608.10401v1 Announce Type: cross Abstract: Intracytoplasmic sperm injection (ICSI) operators frequently adjust the field-of-view (FOV) during procedures, which interrupts workflow and increases procedure time.…
MIDAS: Mutual Information Disentanglement with Uncertainty-Aware Fusion for Incomplete Multimodal Sentiment Analysis
arXiv:2608.09986v1 Announce Type: cross Abstract: Most existing multimodal sentiment analysis approaches assume access to complete multimodal inputs. However, real-world applications frequently encounter incomplete or…
FiGuRO: Intrinsic Dimension Estimation for Multi-Modal Data
arXiv:2608.10857v1 Announce Type: new Abstract: Determining the complexity, or Intrinsic Dimension (ID), of data is fundamental to efficient and interpretable representation learning. This is particularly challenging in…
Beyond Detection Accuracy: Measuring Explanation Cost, Stability, and Utility for Resource-Aware IoT Intrusion Detection
arXiv:2608.10349v1 Announce Type: cross Abstract: Machine-learning intrusion-detection studies commonly emphasize predictive accuracy while treating explanation generation as a computationally free post-processing step.…
Same Targets, Different Computation: How Post-Training Divides Work Across Model Layers
arXiv:2605.07284v2 Announce Type: replace Abstract: A late-layer change learned during post-training may work on the base model's earlier state, or it may depend on earlier computation learned with it. We distinguish…
ReRound: Reconstructive Rounding to Resolve Midpoint Ambiguity in Calibration-Free LLM Quantization
arXiv:2608.11045v1 Announce Type: new Abstract: ReRound (Reconstructive Rounding) is a post-training quantization method that addresses the midpoint ambiguity inherent in standard round-to-nearest (RTN) schemes when…
Comparing SGLD and a fixed-noise Predictor-Corrector adaptation in canonical Joint Energy-Based Models on CIFAR-10
arXiv:2608.05025v2 Announce Type: replace Abstract: Joint Energy-Based Models (JEM) unify classification and generation within a single network and support out-of-distribution (OOD) detection. Canonical JEM training…
Scheduling Mixed RL Rollouts Beyond Prefix Locality
arXiv:2608.11152v1 Announce Type: cross Abstract: Modern reinforcement learning (RL) post-training pipelines for large language models (LLMs) increasingly combine rollout workloads across multiple domains and feedback…
Native Multi-Dimensional Subquadratic Operators via Input Dependent Long Convolutions
arXiv:2607.19378v3 Announce Type: replace Abstract: Subquadratic alternatives to attention require compromises when applied to multi-dimensional data: standard convolutions lack global receptive fields and input…
ChronoSSM: Training for Temporally Aware Representations in Autoregressive State Space Models
arXiv:2608.10120v1 Announce Type: new Abstract: Modern sequence models, from Transformers to State Space Models, have enabled powerful generative modeling across diverse domains, yet they are typically trained to…
UT-ACA: Uncertainty-Triggered Adaptive Context Allocation for Long-Context Inference
arXiv:2603.18446v2 Announce Type: replace-cross Abstract: Long-context inference remains challenging for large language models due to attention dilution and out-of-distribution degradation. Context selection mitigates…
Exact and Asymptotically Complete Robust Verifications of Neural Networks via Ising Solvers
arXiv:2603.00408v4 Announce Type: replace Abstract: We present an Ising-compatible framework for formal neural-network robustness verification under bounded input perturbations. For piecewise-linear activations, the…
Concept Labels Are Not Enough: Rethinking Concept Bottleneck Models through Representation Integrity
arXiv:2510.15770v4 Announce Type: replace-cross Abstract: Although deep neural networks achieve strong predictive performance, their internal reasoning often remains difficult to inspect and control. Concept Bottleneck…
Power law graph attention: exact generalization of scaled dot-product attention, empirical collapse at inference
arXiv:2608.10288v1 Announce Type: new Abstract: The Large Language Model from Power Law Decoder Representations (PLDR-LLM) and its attention, Power Law Graph Attention (PLGA), replace the fixed bilinear form of scaled…
ProTAGAD: A Foundation Model for TAG Anomaly Detection with Decoupled Topological and Textual Prototypes
arXiv:2608.10699v1 Announce Type: new Abstract: Text-Attributed Graphs (TAGs), endowed with abundant textual content along with topological structures, have emerged as a versatile backbone for real-world anomaly…
Quantum Incremental Learning with Mixed State Prototypes
arXiv:2608.10464v1 Announce Type: cross Abstract: Incremental learning models are required to learn new classes sequentially without catastrophic forgetting, while operating under parameter and memory constraints. In…
Exploration-Driven Personalized Federated Reinforcement Learning via Intrinsic Motivation
arXiv:2608.10499v1 Announce Type: new Abstract: Personalized Federated Reinforcement Learning (PFRL) takes a decentralized approach to storing and accessing information based on past experiences while keeping each…
Knowledge-Guided 3D CT Generation: A Conditioning-Centric Taxonomy
arXiv:2608.09992v1 Announce Type: cross Abstract: Controllable generation guided by external knowledge is a key requirement in modern generative deep learning applications, enabling the synthesis of samples with…
Scaling Self-Play with Self-Guidance
arXiv:2604.20209v2 Announce Type: replace Abstract: LLM self-play algorithms are notable in that, in principle, nothing bounds their learning: a Conjecturer model creates problems for a Solver, and both improve…
High-Dimensional Calibration from Swap Regret
arXiv:2505.21460v2 Announce Type: replace Abstract: We study online calibration of multi-dimensional forecasts over an arbitrary convex set $P \subset \mathbb{R}^d$ relative to an arbitrary norm $|\cdot|$. We connect…
TideRL: Boosting Agentic RL Goodput with Readiness-Aware Scheduling
arXiv:2608.10402v1 Announce Type: new Abstract: Reinforcement learning (RL) for large language models is moving toward multi-turn agentic workloads, where rollout tasks repeatedly pause for external environments, resume…
More Accurate, Less Human: Gestalt Grouping in Vision Models
arXiv:2608.10195v1 Announce Type: cross Abstract: Human vision organizes what it sees into wholes: same-colored points group into series, similar marks cohere into categories, and shapes complete into recognizable…
ConVAWG: A Retrieval-Grounded Framework for Controlled Synthetic Dialogue Generation in Violence Against Women and Girls
arXiv:2608.11200v1 Announce Type: cross Abstract: Synthetic dialogue generation offers a way to study conversational dynamics in sensitive domains where real data are difficult to access, release, or annotate. The…
HyperShape: Hyperelasticity Across Diverse Shapes
arXiv:2608.09938v1 Announce Type: cross Abstract: Hyperelastic deformations are highly sensitive to domain geometry and boundary conditions, making generalization across both a critical capability for neural operators…
Model Multiplicity and Predictive Arbitrariness in Recidivism Risk Assessment
arXiv:2606.02198v2 Announce Type: replace Abstract: Prediction tasks over individual futures, which are inherently noisy, often admit multiple similarly accurate models. When these models produce different predictions…
Long-Time Trajectory Approximation via SA-NODEs: Model Predictive and Floquet Strategies
arXiv:2608.10738v1 Announce Type: new Abstract: We study the approximation of dynamical systems by semi-autonomous neural ordinary differential equations (SA-NODEs) over long time horizons. For a single network trained…
From Prediction to Incrementality: Causal Optimization for Large-Scale Targeting and Recommendation
arXiv:2608.10182v1 Announce Type: new Abstract: Large-scale targeting and recommendation systems are typically built around predictive scores fed into heuristic or local allocation. When the business goal is incremental…
Grounded Post-Training with Hard Examples for Reducing Hallucination in Multimodal Large Language Models
arXiv:2605.16411v3 Announce Type: replace-cross Abstract: Hallucination remains a fundamental challenge in vision-language models (VLMs), where autoregressive generation may produce linguistically plausible yet…
P3CA: Encoder-Agnostic Interpretation of Vision Foundation Model Embeddings via Spatial Probing
arXiv:2608.10131v1 Announce Type: cross Abstract: Vision foundation models are increasingly used as reusable encoders in medical image computing, yet their high-dimensional spatial embeddings are difficult to inspect…
Topological Feasibility Guarantees for Differentiable Predictive Control
arXiv:2608.10332v1 Announce Type: cross Abstract: Differentiable predictive control (DPC), a self-supervised learning approach for approximating explicit model predictive control (MPC) policies, offers significant…
An Exact Instrument for State Usage in Selective State-Space Models, and the Input-Driven Migration It Reveals
arXiv:2607.11796v2 Announce Type: replace Abstract: Selective state-space models such as Mamba route information through a bank of first-order modes whose input coupling is set by a learned selection mechanism. We give…
Loop, Think, & Generalize: Implicit Reasoning in Recurrent-Depth Transformers
arXiv:2604.07822v2 Announce Type: replace-cross Abstract: We study implicit reasoning, i.e. the ability to combine knowledge or rules within a single forward pass. While transformer-based large language models store…
Validated Synthetic Patient Generation for Small Longitudinal Cohorts: Coagulation Dynamics Across Pregnancy
arXiv:2604.07557v2 Announce Type: replace Abstract: Small longitudinal cohorts, common in maternal health, rare diseases, and early-phase trials, limit computational modeling because enrollment is slow and the data are…
DQS: A Low-Budget Query Strategy for Enhancing Unsupervised Data-driven Anomaly Detection Approaches
arXiv:2509.05663v4 Announce Type: replace Abstract: Truly unsupervised approaches for time series anomaly detection are rare in the literature. Those that exist suffer from a poorly set threshold, which hampers…
Measuring Semantic Abstractness of SAE Features via Nonlocality
arXiv:2608.10537v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) have helped uncover mechanistic explanations for LLM behaviours such as reasoning, jailbreaking etc., via understanding the corresponding…
VDC-Agent: When Video Detailed Captioners Evolve Themselves via Agentic Self-Reflection
arXiv:2511.19436v2 Announce Type: replace-cross Abstract: Existing Video Detailed Captioning (VDC) methods predominantly rely on costly human annotations or distillation from powerful proprietary models, creating a…
HIPNO: Symmetry-Aware Physics-Informed Neural Operators for Noninvasive Hemodynamic Inference
arXiv:2608.10011v1 Announce Type: cross Abstract: Continuous hemodynamic monitoring guides treatment decisions in surgery and intensive care. However, gold-standard signals are only measured in severe cases due to risks…
Finding the Signal in the Spam: Jointly Learning Rewards and Worker Reliability from Pairwise Comparisons
arXiv:2608.10045v1 Announce Type: new Abstract: The problem of learning from pairwise comparisons has been widely studied across many domains such as recommendation systems, social choice, and more recently, fine-tuning…
Predictive Entropy as a Joint Screen for Error and Paraphrase Instability in Medical Vision-Language Models
arXiv:2604.08941v2 Announce Type: replace Abstract: Medical Vision-Language Models (VLMs) answering binary presence questions on chest radiographs can fail in two linked ways: they are confidently wrong, and they change…
AgentSnare: Learning to Delay, Divert, and Defuse Autonomous Penetration Agents
arXiv:2607.26998v3 Announce Type: replace-cross Abstract: Large language model (LLM) agents automate penetration testing through an observation-action loop, selecting actions based on observations returned by tools.…
MERA: Model Evolution and Routing with Skill Adaptation for Agentic Systems at Scale
arXiv:2608.10333v1 Announce Type: new Abstract: LLM agents execute heterogeneous sequences of model calls within a single task: some invocations require careful reasoning, while others are structured steps such as…
Choosing a JPEG Decoder for PyTorch DataLoaders: Workload-Specific Throughput on Four CPUs
arXiv:2605.08731v3 Announce Type: replace-cross Abstract: A JPEG decoder benchmark can combine worker counts, CPUs, and datasets in one large result matrix. We simplify that comparison by fixing a PyTorch DataLoader at…
Convergence of Sign-based Random Reshuffling Algorithms for Nonconvex Optimization
arXiv:2310.15976v4 Announce Type: replace Abstract: signSGD is attractive in nonconvex optimization because it communicates sign-valued rather than full-precision gradients. Several standard analyses assume independent…
On The Statistical Limits of Self-Improving Agents
arXiv:2510.04399v3 Announce Type: replace-cross Abstract: We develop a learning-theoretic framework for analyzing self-improving agents by decomposing self-modification into five axes. Within this framework, we prove a…
A Tale of Two Temperatures: Simple, Efficient, and Diverse Sampling from Diffusion Language Models
arXiv:2604.09921v2 Announce Type: replace Abstract: Much work has been done on designing fast and accurate sampling for diffusion language models (dLLMs). However, these efforts have largely focused on the tradeoff…
Multi-Granular Rationale-Guided Molecular LLM for Property Prediction
arXiv:2608.10480v1 Announce Type: cross Abstract: Large language models (LLMs) are widely applied across chemical tasks, such as molecular property prediction, which underpins drug discovery. Molecular LLMs represent a…
Local Fr\'echet functional regression in manifolds from time-correlated bivariate curve data
arXiv:2505.05168v4 Announce Type: replace-cross Abstract: Under mild conditions, a least-squares local linear Fr\'echet curve predictor is derived for a response and a regressor evaluated in a separable Hilbert space.…
SQuaT: Self-Supervised Knowledge Distillation via Student-Aware Quantized Teacher Features
arXiv:2608.10709v1 Announce Type: new Abstract: Quantization-Aware Training (QAT) enables the deployment of quantized models with minimal accuracy degradation. However, in practical scenarios, training labels are often…
Can Computational Reducibility Lead to Transferable Models for Graph Combinatorial Optimization?
arXiv:2603.02462v2 Announce Type: replace Abstract: A key challenge in developing unified neural solvers for combinatorial optimization (CO) is the efficient generalization of models from a given set of tasks to new…
Energy and Performance Benchmarking of Deep Learning Models for Breast Cancer Detection
arXiv:2608.09996v1 Announce Type: cross Abstract: Recent advances in machine learning have greatly improved breast cancer detection, enabling more accurate and timely diagnosis. Deep learning (DL) models show strong…
Regression and Classification with Single-Qubit Quantum Neural Networks
arXiv:2412.09486v2 Announce Type: replace-cross Abstract: The literature reflects a mutually beneficial relationship between machine learning and quantum computing, where progress in one field frequently drives…
ELVAE: Evidential Learning-Based Variational Autoencoder for Uncertainty-Aware Generation
arXiv:2608.10398v1 Announce Type: new Abstract: Variational autoencoders generate samples from probabilistic latent representations but do not distinguish uncertainty about the latent location from variability around…
Emergent Neural Network Mechanisms for Generalization to Objects in Novel Orientations
arXiv:2109.13445v3 Announce Type: replace-cross Abstract: The capability of Deep Neural Networks (DNNs) to recognize objects in orientations outside the distribution of the training data is not well understood. We…
Bandwidth-Efficient Multi-Agent Communication through Information Bottleneck and Vector Quantization
arXiv:2602.02035v2 Announce Type: replace-cross Abstract: Multi-agent reinforcement learning systems deployed in real-world robotics applications face severe communication constraints that significantly impact…
Dual Space Preconditioning for Gradient Descent in the Overparameterized Regime
arXiv:2603.10485v3 Announce Type: replace-cross Abstract: In this work, we study the convergence properties of the Dual Space Preconditioned Gradient Descent, encompassing optimizers such as Normalized Gradient Descent…
MRIComp4Flow: Compression of 3D Brain MRI for Training Multi-Modal Generative Models
arXiv:2608.10291v1 Announce Type: cross Abstract: Large-scale multi-modal MRI datasets impose substantial storage and I/O costs, limiting the training of 3D generative models on commodity infrastructure. While lossy…
TACTICL: Task-Aware Compression of Tabular ICL Models
arXiv:2608.10837v1 Announce Type: new Abstract: The strong performance of foundation models for tabular tasks comes at substantial inference costs. Distilling models into task-specific architectures reduces model size…
SeFoRA: Sketch-Aggregated Federated Low-Rank Adaptation with Heterogeneous Client Ranks
arXiv:2608.10144v1 Announce Type: new Abstract: We consider federated parameter efficient fine-tuning of large neural networks with low-rank adaptation (LoRA,~Hu et al.\ 2022). Combining LoRA with federated PEFT…
Deep Learning-Based Statistical Downscaling of Sea Surface Temperature Using a Residual Corrective Neural Network
arXiv:2608.10022v1 Announce Type: cross Abstract: The large-scale oceanic and atmospheric forecasts provided by global climate models typically lack sufficient resolution to accurately capture the response of the…
Wiring Beats Blending: What Transfers Between Transformer Sizes -- and What Doesn't
arXiv:2608.02829v2 Announce Type: replace Abstract: Model families are typically trained size by size, each from scratch. Can apretrained large model instead be converted into a smaller sibling? Wecharacterize the…
Partially Observable Learning for Multi-Platform Dispatch Optimization
arXiv:2608.10897v1 Announce Type: new Abstract: Instant delivery platforms have become a critical component of urban logistics, increasingly relying on crowdsourced couriers to fulfill highly dynamic orders. In…
CARB: A Characterization-Guided Framework for CNN Inference Cost Prediction and Deployment Screening
arXiv:2608.10506v1 Announce Type: cross Abstract: Accurate pre-deployment estimation of CNN inference cost--energy, latency, and peak memory--is increasingly critical as models are deployed on resource-constrained GPU…
TS-Mob: Social and Geographical-Aware Time Series Foundation-Model Framework for Human Mobility Prediction
arXiv:2507.00945v3 Announce Type: replace Abstract: Short-term forecasting of aggregated human mobility flows supports urban planning, intelligent transportation systems, and emergency response, yet existing models…
Measuring and Reducing WebGPU Dispatch Overhead for LLM Inference
arXiv:2608.08730v2 Announce Type: replace Abstract: Large Language Models are deployed to multiple types of environments, from internet browsers to edge devices, and WebGPU serves as a modern cross-platform standard.…
Generalized Linear Markov Decision Process
arXiv:2506.00818v2 Announce Type: replace-cross Abstract: Offline reinforcement learning for longitudinal studies often faces two linked challenges: rewards may be binary or bounded, and reward observations may be…
Intrinsic Structure: Spectral Identifiability for Mechanistic Interpretability
arXiv:2608.10172v1 Announce Type: new Abstract: Mechanistic interpretability explains models by identifying circuits inside them, but has no way to tell whether a circuit is a property of the model or an artifact of the…
ELMER: Evolutionary Language Model that Explores and Refines
arXiv:2608.10196v1 Announce Type: new Abstract: Program evolution can measure whether a mutation helped, but it rarely controls how far the mutation moves in behavior space. Syntactic edit size is an unreliable proxy: a…
HyWA: Architecture-Preserving Personalized Voice Activity Detection for Full-Duplex Voice Assistants
arXiv:2510.12947v3 Announce Type: replace-cross Abstract: Voice activity detection (VAD) serves as an early gate in voice-assistant pipelines for smart devices. Because conventional VADs respond to speech from any…
UserToolBench: A User-Profile-Hidden Benchmark for Personalized Decision Making in Tool-Use LLMs
arXiv:2608.10042v1 Announce Type: new Abstract: Tool-use LLMs are increasingly asked to act on users' behalf, but existing benchmarks usually focus on profile recall, style imitation, generic tool use, or response-level…
TSCoNet: A Two-Stage Copula CNN-LSTM for Uncertainty-Aware Spatio-Temporal Forecasting
arXiv:2607.10410v2 Announce Type: replace-cross Abstract: Reliable forecasting of several interrelated environmental variables - such as regional precipitation and temperature, or other correlated geophysical fields -…
Why Do Safety Guardrails Degrade Across Languages?
arXiv:2605.17173v2 Announce Type: replace-cross Abstract: Large language models exhibit safety degradation in non-English languages. Standard evaluation relies on Jailbreak Success Rate (JSR), which confounds several…
Quantifying the noise sensitivity of the Wasserstein metric for images
arXiv:2510.01015v3 Announce Type: cross Abstract: Wasserstein metrics are increasingly adopted as similarity scores for images. We consider the sensitivity of Wasserstein metrics with respect to pixel-wise additive…
Recent advances in weakly supervised learning: New supervision paradigms, assumption relaxations, and practical solutions
arXiv:2608.06896v2 Announce Type: replace Abstract: Deep learning has achieved great success in recent years thanks to the availability of high-quality, well-annotated training data. However, this requirement is often…
A case study of evaluating AI agents on a neuroscience data-to-discovery pipeline
arXiv:2606.07718v2 Announce Type: replace-cross Abstract: Agentic AI offers a promising path to automating software development bottlenecks in scientific research pipelines, particularly for stages that take domain…
ReOrder-OPD:Reliability-Aware Prompt Ordering for On-Policy Distillation
arXiv:2608.10905v1 Announce Type: new Abstract: On-policy distillation (OPD) applies token-level teacher supervision to student-generated trajectories, but this supervision is not always reliable. Existing methods use…
SeFaR: Semantic Feature-aware Robustness Testing of Deep Neural Networks
arXiv:2608.10289v1 Announce Type: cross Abstract: Deep neural networks are increasingly deployed in safety-critical domains as perception modules, where failures are often caused due to rare and under-represented…
FlowScout: From Execution Feedback to Reliable Tool-Using Agent Workflows
arXiv:2608.10039v1 Announce Type: new Abstract: Agentic workflows have become an important abstraction for building reliable LLM-based automation systems by organizing large language models (LLMs), tools, and control…
UniScale: Synergistic Entire Space Data and Model Scaling for Search Ranking
arXiv:2603.24226v4 Announce Type: replace-cross Abstract: Recent advances in Large Language Models (LLMs) have inspired a surge of scaling research in industrial search, advertising, and recommendation systems. However,…
Spectral Embeddings of Degree-$\alpha$ Laplacians in Random Dot Product Graphs
arXiv:2608.10845v1 Announce Type: cross Abstract: Spectral clustering methods for network data are commonly based on a few matrix representations, such as the adjacency matrix and the symmetric Laplacian. We study a…
Detecting Soft Skills in ML Engineering Roles CVs
arXiv:2608.10046v1 Announce Type: new Abstract: Soft skills shape collaboration among ML engineers, data scientists, and software engineers building ML-enabled systems, yet what we know about them comes almost entirely…
Compute-Optimal Is Not Cluster-Optimal: Systems-Aware Scaling for Sparse Mixture-of-Experts
arXiv:2608.10605v1 Announce Type: new Abstract: In large-scale pretraining, the algorithm, architecture, and systems decisions are conventionally made in disconnected stages. A scaling law stage selects an architecture…
Leak It: Per-Document Extraction Beyond Aggregate Membership Inference
arXiv:2608.00144v2 Announce Type: replace Abstract: Membership inference (MIA) on language models is usually summarised by aggregate ROC-AUC, but such evaluations are confounded: model-free blind baselines can separate…
REATS: LLM Reasoning-based Ensemble Learning for Adaptive Time Series Forecasting
arXiv:2608.10149v1 Announce Type: new Abstract: Due to the diversity of real-world time series, no single forecasting model consistently dominates across all samples. Ensemble learning addresses this by combining…
Inverse Design of Inorganic Compounds with Generative AI
arXiv:2604.11827v2 Announce Type: replace-cross Abstract: Machine learning is revolutionizing chemistry. Beyond the value of predictive models accelerating virtual screening, generative AI aims at enabling inverse…
When Interpretability Is Unequally Distributed: Fairness in Hybrid Interpretable Models
arXiv:2605.28626v2 Announce Type: replace Abstract: Hybrid interpretable models combine a transparent component with a black-box model by assigning some examples to the former and deferring the rest to the latter. While…
Seq2Synth: Benchmarking Temporal Fidelity in Synthetic Sequential Tabular Data
arXiv:2607.15606v2 Announce Type: replace Abstract: Synthetic sequential tabular data are increasingly used for privacy-preserving data sharing and data-driven research, but evaluating their fidelity remains difficult…
InSight-doc: Agentic Visual Perception for Long-Document Understanding
arXiv:2608.10628v1 Announce Type: cross Abstract: Long-document understanding often requires reasoning over many visually rich pages, making inference costly and prone to context rot. In this work, we propose…
Physics-Informed Condition Monitoring of SiC Power Modules
arXiv:2608.08363v2 Announce Type: replace-cross Abstract: Silicon carbide (SiC) power modules are increasingly deployed in automotive traction inverters, where condition monitoring is essential to prevent in-service…
Representation and Invariance in Reinforcement Learning
arXiv:2112.07752v5 Announce Type: replace-cross Abstract: Researchers have formalized reinforcement learning (RL) in different ways. If an agent in one RL framework is to run within another RL framework's environments,…
Divergent Response Modes in Frontier Language Models Under Steering Pressure
arXiv:2608.06578v1 Announce Type: cross Abstract: Frontier language models are trained using distinct data, objectives, and safety pipelines. Whether these differences produce measurably different behaviors under…
Do AI weather models miss extremes?
arXiv:2608.09972v1 Announce Type: cross Abstract: First-generation AI weather models are often reported to underperform at extremes, mostly in reanalysis-based evaluations of deterministic regression systems. We verify…
Stochastic Emulation of a Fully Coupled Preindustrial E3SMv3 Simulation
arXiv:2608.10277v1 Announce Type: cross Abstract: We present a stochastic coupled emulator of E3SM version 3, built on the SamudrACE framework, which couples an atmosphere emulator (ACE2) with a full-depth ocean…
Population-Aware Physics-Informed Neural Particle Flow for Robust Spacecraft Bayesian Navigation
arXiv:2606.10959v2 Announce Type: replace Abstract: Spacecraft navigation often requires Bayesian inference from sparse nonlinear measurements that produce curved, multimodal, or geometrically constrained posterior…
URS: A Unified Neural Routing Solver for Cross-Problem Zero-Shot Generalization
arXiv:2509.23413v3 Announce Type: replace Abstract: Multi-task neural routing solvers have emerged as a promising paradigm for their ability to solve multiple vehicle routing problems (VRPs) using a single model.…
KrishokChat: A Provenance-Traceable Multi-Task Bengali Agricultural Benchmark with Safety-Critical Chemical Advisory
arXiv:2606.29243v2 Announce Type: replace Abstract: We introduce KrishokChat, an 85,979-instance Bengali agricultural benchmark built from 284 government publications, 13 institutions, and six regional dialects. The…
Where Flow Matching Leaks: Characterising Membership Signals Along the Interpolation Path
arXiv:2606.07271v3 Announce Type: replace Abstract: Understanding memorization in generative models remains challenging, with implications for copyright and privacy. Beyond verbatim reproduction, models can encode…
Beyond a Bag of Features: Set-Level Instability in Sparse Autoencoders
arXiv:2608.11197v1 Announce Type: new Abstract: Shani et al. (2026) show that LLM representations broadly recover human category boundaries, while failing to reflect fine-grained typicality structure. Their analysis…
Testing when adaptive data acquisition can replace fixed measurement plans
arXiv:2607.27651v2 Announce Type: replace Abstract: Learned rules select samples for follow-up measurements in high-throughput experiments. Predicted value does not justify replacing a fixed plan. We introduce the…
Flow Straight to Reality: Perceptually Consistent Flow Matching for Efficient Image Restoration
arXiv:2608.10544v1 Announce Type: cross Abstract: Image restoration is fundamentally constrained by the tradeoff between distortion and perception: minimizing pixel-wise error yields over-smoothed results, whereas…
How Robust Are LLMs to Vietnamese Dialects?
arXiv:2608.10414v1 Announce Type: cross Abstract: Large Language Models (LLMs) are typically evaluated on standard written Vietnamese, yet everyday communication frequently involves regional dialects that preserve…
Benchmarking LLM-Guided Control-Plane Policies for Backend Fault Isolation in HAProxy
arXiv:2608.10532v1 Announce Type: cross Abstract: Static load balancers cannot mitigate a backend that is degraded rather than down: round-robin and least-connections keep routing traffic to a server returning HTTP 500s…
Efficient Weak-Entropy PINN for Solving Hyperbolic Conservation Laws
arXiv:2608.10389v1 Announce Type: cross Abstract: In recent years, neural networks have significantly advanced numerical solutions of partial differential equations (PDEs). However, solving PDEs with discontinuous…
Behavioral Inference at Scale: The Fundamental Asymmetry Between Motivations and Belief Systems
arXiv:2509.05624v3 Announce Type: replace-cross Abstract: How much information about an agent's underlying values can be recovered from its observable behavior? This question matters for any approach that infers agent…
A Systematic Sample Size Analysis of ML-Based Path Loss Prediction for LPWAN
arXiv:2608.11083v1 Announce Type: cross Abstract: Low Power Wide Area Networks like LoRa are increasingly deployed for smart city applications, requiring accurate path loss prediction for effective network planning.…
GARLIC: Graph Attention-based Relational Learning of Multivariate Time Series in Intensive Care
arXiv:2608.10969v1 Announce Type: new Abstract: Healthcare data, such as Intensive Care Unit (ICU) records, comprise heterogeneous multivariate time series sampled at irregular intervals with pervasive missingness.…
Fisher8: Stabilizing Neural Heteroscedastic Regression via Output-Layer Fisher Geometry
arXiv:2608.10374v1 Announce Type: new Abstract: Training neural networks to jointly predict mean and uncertainty estimates from noisy observations can be unstable, prompting a series of independent stabilization…
Automated Data Enrichment using Confidence-Aware Fine-Grained Debate among Open-Source LLMs for Mental Health and Online Safety
arXiv:2512.06227v3 Announce Type: replace-cross Abstract: Real-world indicators play an important role in many Natural Language Processing (NLP) applications, such as life events for mental health analysis and risky…
Proteo-R1: Reasoning Foundation Models for De Novo Protein Design
arXiv:2605.02937v2 Announce Type: replace Abstract: Deep learning in de novo protein design has achieved atomic-level fidelity. However, existing models remain largely non-deliberative: they directly synthesize…
DEFT: Data-Efficient Frequency-domain Top-k Sampling via Inverse Discrete Fourier Transform for Spatiotemporal Dynamical Systems Modeling
arXiv:2608.11019v1 Announce Type: new Abstract: Modeling spatiotemporal dynamical systems governed by partial differential equations (PDEs) poses two major challenges: it either requires expensive physics-based…
On Effectiveness and Efficiency of Agentic Tool-calling and RL Training
arXiv:2606.00135v2 Announce Type: replace Abstract: Tool-calling is a central component of modern large language model (LLM) agents, equipping them with skills beyond their parametric knowledge. This paper studies…
IADD-TR: Intervention-Aware Dynamics Decoupling with Targeted Regularization for Model-Based Reinforcement Learning
arXiv:2608.10634v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL), which learns environment dynamics to generate synthetic experience, is a promising approach to sample-efficient decision making.…
Lipschitz Dueling Bandits over Continuous Action Spaces
arXiv:2604.00523v2 Announce Type: replace Abstract: We study for the first time, stochastic dueling bandits over continuous action spaces with Lipschitz structure, where feedback is purely comparative. While dueling…
ChemWorld: Programmable Chemical Worlds for Controlled and Replayable Agent Experimentation
arXiv:2608.10792v1 Announce Type: cross Abstract: Autonomous chemistry increasingly depends on environments in which agents can repeatedly act, observe, and adapt.Physical laboratories provide essential real-material…
Hierarchical Empirical-Bayes Naive Bayes: Minimax Smoothing and Calibration with AODE Extension
arXiv:2608.11162v1 Announce Type: new Abstract: The Naive Bayes (NB) classifier remains a standard choice for categorical data, yet its widely used smoothing rules, such as Laplace, Lidstone, Krichevsky-Trofimov, and…
Do LLM Recommenders Know When They're Hallucinating? Auditing Confidence Calibration in Catalog Faithfulness
arXiv:2608.10008v1 Announce Type: cross Abstract: LLM recommenders for top-$K$ item suggestion regularly emit titles outside the target catalog. Prior audits measure this as a binary out-of-domain rate; none ask whether…
Why Does CLAUDE.md Keep Growing? Catastrophic Remembering in Agentic Coding
arXiv:2608.11095v1 Announce Type: cross Abstract: Agentic coding READMEs like CLAUDE.md grow without bound in real repositories, stopping only when the repository retires or someone rewrites the file wholesale. We trace…
Generator-Guided Inverse Sampling for L\'evy-Driven Generative Models
arXiv:2608.10384v1 Announce Type: new Abstract: This paper studies inverse sampling for L\'evy-driven generative models from the perspective of Markov generators. Unlike conventional diffusion models, L\'evy-driven…
The Matching Principle: When Does a Training Penalty Cover Deployment Shift?
arXiv:2605.22800v3 Announce Type: replace Abstract: Ordinary training optimises the task loss and then stops. It never pays for internal representation energy: Jacobians can stay large in directions that never helped…
Deciding When to Switch: E-Processes for Adaptive Minimax Training for Generative Adversarial Nets
arXiv:2608.10096v1 Announce Type: cross Abstract: Modern data science increasingly gives rise to hypothesis-testing problems that are not naturally formulated in terms of parameters within prespecified statistical…
BreastMammo and DenseMammo: Benchmarks for Mammography Domain Generalization
arXiv:2608.10271v1 Announce Type: cross Abstract: Breast density classification is a critical component of breast cancer risk assessment, yet AI models often struggle to generalize across clinical sites due to…
Clarity: The Flexibility-Interpretability Trade-Off in Sparsity-aware Concept Bottleneck Models
arXiv:2601.21944v3 Announce Type: replace Abstract: The widespread adoption of deep learning models in computer vision has intensified concerns about interpretability. Despite strong performance, these models are often…
Delays in Spiking Neural Networks: A State Space Model Approach
arXiv:2512.01906v3 Announce Type: replace Abstract: Spiking neural networks (SNNs) are biologically inspired, event-driven models suited for temporal data processing and energy-efficient neuromorphic computing. In SNNs,…
Adaptive Supervised Anchoring for On-Policy Self-Distillation
arXiv:2608.07935v2 Announce Type: replace Abstract: On-policy self-distillation (OPSD) adapts a language model by distilling guidance from a frozen teacher on trajectories sampled from the student. Its effectiveness,…
Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint
arXiv:2608.09998v1 Announce Type: cross Abstract: Artificial Intelligence (AI) and Machine Learning (ML) have become powerful tools for supporting and automating complex human tasks. Despite their benefits, growing…
An adaptive and evolvable deep reinforcement learning framework for weather prediction
arXiv:2608.09948v1 Announce Type: cross Abstract: No single AI weather model excels at all variables, pressure levels, and lead times. Rather than building yet another architecture, we reframe the forecasting problem as…
Risk-Averse Wasserstein Distributionally Robust Online Learning
arXiv:2602.20403v2 Announce Type: replace Abstract: We study distributionally robust online learning, where a risk-averse learner updates decisions sequentially to guard against worst-case distributions drawn from a…
Physics-Informed Machine Learning in Prognostics and Health Management: A Systematic Literature Review
arXiv:2608.10047v1 Announce Type: new Abstract: In modern industry, keeping complex systems reliable, safe, and efficient hinges on Prognostics and Health Management (PHM). Machine Learning (ML) has largely driven…
HoloQ-VLA: Uniform W4A4 Quantization of Vision-Language-Action Models
arXiv:2605.28803v3 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models unify perception, reasoning, and control in a single policy, but their multi-billion-parameter backbones and diffusion-based…
ConTact: Contact-First Antibody CDR Design via Explicit Interface Reasoning
arXiv:2605.21600v3 Announce Type: replace Abstract: Computational antibody CDR design methods condition on antigen structure to generate binding loops. Yet, the existing architectures conflate two fundamentally distinct…
Toward Human Rights Benchmarking for LLMs: A Pilot Methodology
arXiv:2608.10268v1 Announce Type: new Abstract: Large language models (LLMs) increasingly mediate legal determinations over what human rights are realized, and how. Yet, no evaluation benchmark exists to assess whether…
Market Design for AI: Beyond the Copyright Binary
arXiv:2606.12260v3 Announce Type: replace-cross Abstract: How can we design a market of human-generated content for use in training AI models that both enables technological progress and preserves individual incentives…
When Chain-of-Thought Helps and When It Hurts: An Empirical Investigation of the Serial-Depth Bottleneck in LLM Reasoning
arXiv:2608.09942v1 Announce Type: cross Abstract: It is widely assumed that chain-of-thought (CoT) prompting universally improves LLM reasoning. We investigate this through the conceptual framework of the H_dp bandwidth…
Gromov-Wasserstein Quantization and Clustering: Structure, Rates, and Algorithms
arXiv:2608.11016v1 Announce Type: cross Abstract: Clustering is a fundamental class of data analysis techniques with the most important representatives being centroid-based methods like $k$-means. Such methods are…
Logit-Boundary Geometric Belief Interfaces and Sparse Sheaf-Enclave Protocols: A Self-Contained Substrate for Secure Network Electronic Health Record (EHR) Interoperability
arXiv:2608.10300v1 Announce Type: cross Abstract: Electronic health-record interoperability is a boundary problem: legacy systems, generative models, terminology services, identity systems, and human reviewers may each…
Sequential Modality Dropout for Robust Multi-Modal Sequential Recommendation
arXiv:2608.10240v1 Announce Type: cross Abstract: Multi-modal sequential recommenders assume every item carries every modality, but real product catalogs often miss images or text, and a model trained on complete data…
ProbGuard: Calibrated Safety Risk Estimation from LLM Output Distributions
arXiv:2608.10621v1 Announce Type: new Abstract: Recent research on Large Language Model (LLM) safety has widely adopted guardrails to identify unsafe LLM outputs. Existing guardrails typically formulate safety…
Information Bottleneck under Perfect Privacy
arXiv:2608.11003v1 Announce Type: cross Abstract: In this work, we study the information bottleneck under perfect privacy, with particular emphasis on the active-rate regime, where the representation-rate constraint is…
Bayesian Federated Cause-of-Death Classification and Quantification Under Distribution Shift
arXiv:2505.02257v2 Announce Type: replace-cross Abstract: In regions lacking medically certified causes of death, verbal autopsy (VA) is a widely used tool to ascertain the cause of death through interviews with…
On the Importance of Geometric Nonlinearity and Temperature-Dependent Properties in Multi-Material Thermo-Mechanical Topology Optimization
arXiv:2608.10344v1 Announce Type: cross Abstract: Thermo-mechanical compliant devices are commonly designed with small-strain linear elasticity and temperature-independent material properties, even though they might…
MARCO: Click-Intent Decomposition for Calibrated Ads Conversion Prediction
arXiv:2608.10562v1 Announce Type: new Abstract: Not all clicks are equal. Industrial ads ranking decouples conversion probability into click-through rate (CTR) and post-click conversion rate (CVR), yet treats every…
$\beta$-VAEs as Effective Theories: Tolerance-Dependent Dimension
arXiv:2608.10599v1 Announce Type: new Abstract: In a $\beta$-VAE, increasing the regularization strength acts as a spectral cutoff by collapsing low-utility latent coordinates. In the linear Gaussian VAE, the collapse…
Observational Policy Ranking for SMB Financial Guidance from Multi-Action Accounting Logs
arXiv:2608.10050v1 Announce Type: new Abstract: Small and medium-sized businesses need timely financial guidance, yet historical accounting logs record self-selected and often co-occurring business changes rather than…
A matched-integrator evaluation of Hamiltonian neural networks on pendulum and Kepler dynamics
arXiv:2608.10235v1 Announce Type: new Abstract: Hamiltonian Neural Networks (HNNs) parameterize conservative dynamics through a learned scalar Hamiltonian, providing an architectural prior that is absent from generic…
VIDS-Seg: Towards Reliable Uncertainty Quantification in Pediatric Cardiac Ultrasound Segmentation
arXiv:2608.10903v1 Announce Type: cross Abstract: Reliable clinical deployment of machine learning requires models that know when they are likely to fail, particularly for subgroups underrepresented in training data. A…
Batch Size or Negatives? A Selection Rule for Memory-Constrained Recommender Training
arXiv:2608.11061v1 Announce Type: new Abstract: Large-scale neural recommender systems are typically trained with a softmax cross-entropy objective over the full item vocabulary. For a typical large number of possible…
RankFormer: A Propose-then-Select Transformer for Multi-Agent Multimodal Trajectory Prediction
arXiv:2604.07126v3 Announce Type: replace-cross Abstract: Predicting traffic agent trajectories plays an important role in autonomous driving, traffic operations, transportation safety analysis, etc. Although many deep…
Optimize Cheap, Deploy Strong: Cost-Aware Cross-Tier Transfer for Evolutionary Optimization
arXiv:2608.10694v1 Announce Type: new Abstract: Evolutionary optimization of LLM prompts and agentic programs (e.g., GEPA) is dominated by fitness evaluation: scoring each candidate runs an answering LLM over a…
Conditional Independence Tests for Constraint-Based Causal Discovery: A Survey
arXiv:2608.11156v1 Announce Type: cross Abstract: Conditional Independence (CI) tests are the statistical engine of constraint-based causal discovery: in algorithms such as PC (Peter-Clark) and FCI (Fast Causal…
Infra-Bayesian Reinforcement Learning Agents Outperform Classical RL For Worst-Case Robustness
arXiv:2605.23146v3 Announce Type: replace Abstract: Classical reinforcement learning assumes the agent interacts with a fixed environment whose behavior does not depend on the agent's policy. This assumption breaks down…
Derivative Computation in PINNs: Automatic Differentiation, Finite Differences and Beyond
arXiv:2608.11020v1 Announce Type: new Abstract: We systematically investigate finite-difference (FD) derivative computation in Physics-Informed Neural Networks (PINNs) as an alternative to automatic differentiation…
UniProbe: A Learnable Token-Level Hallucination Detector for Large VLMs using Multi-Structural Internal Representations
arXiv:2608.10835v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) achieve impressive visual reasoning and dialogue capabilities, yet frequently hallucinate content unsupported by the visual input.…
Dreamer-SAC: Off-Policy Learning in Latent World Models for Sample-Efficient Autonomous Driving
arXiv:2608.10386v1 Announce Type: new Abstract: Sample-efficient reinforcement learning for autonomous driving is often limited by the trade-off between data efficiency and model bias. While world models reduce the…
Detecting an Effect Is Not Learning to Act on It: A Reward-SNR Floor for LLM Acquisition Agents
arXiv:2608.10441v1 Announce Type: new Abstract: Many pipelines can pay a per-example cost to acquire an auxiliary, model-derived observation -- an LLM's structured reasoning, a slow oracle, an expensive measurement --…
A variational Bayes approach to inference for low-dimensional parameters in high-dimensional linear regression
arXiv:2406.12659v3 Announce Type: replace-cross Abstract: We propose a scalable variational Bayes method for statistical inference for a single or pre-specified low-dimensional subset of the coordinates of a…
Your LLM, Your Style: Behavioral Mode Axes for LLM Behavioral Control
arXiv:2608.10703v1 Announce Type: new Abstract: Large language models (LLMs) increasingly act in interactive settings where their behavioral styles affect user experience, safety, and downstream decision making.…
Diffusion-Based Impedance Learning for Contact-Rich Manipulation Tasks
arXiv:2509.19696v4 Announce Type: replace-cross Abstract: Learning-based methods excel at robot motion generation but remain limited in contact-rich physical interaction. Impedance control provides stable and safe…
Riemann GeoResolver: A Non-Euclidean Attention Framework from Euclidean Resolver to Hyperbolic-Spherical Geometry
arXiv:2608.10416v1 Announce Type: cross Abstract: We present a theoretical foundation for inverse-distance attention, from its Euclidean prototype (Resolver) to its non-Euclidean realization (Riemann GeoResolver). The…
Two-stage Odd Residual Flows for Mean-Preserving Probabilistic Time Series Forecasting
arXiv:2608.11114v1 Announce Type: new Abstract: Probabilistic forecasting plays an essential role in risk-sensitive decision-making, particularly in long-horizon settings. However, existing approaches often face a…
Physics-informed Diffusion Generative Model for Time-Series Data Synthesis in Dynamic Systems
arXiv:2608.10941v1 Announce Type: new Abstract: Industrial time-series signals, such as turbine temperature and rotational speed in aero-engines, are essential for monitoring the health and operational status of complex…
Link-adaptive digital twin for robust physical-layer modeling in hybrid-amplified ultra-wideband optical networks
arXiv:2608.10517v1 Announce Type: cross Abstract: Accurate physical-layer modeling is increasingly essential for reliable ultra-wideband operation and capacity optimization, especially under the intensified…
Foundations of Equivariant Deep Learning: Unifying Graph and Sheaf Neural Networks
arXiv:2607.03798v4 Announce Type: replace Abstract: Symmetry is everywhere in nature and society. Geometric deep learning builds architectures respecting group symmetries, whereas topological deep learning organizes…
Population-Level Generative Modeling for Ranking Data
arXiv:2608.08422v2 Announce Type: replace-cross Abstract: Ranking data arise in scientific and machine learning applications, including recommendation systems, information retrieval, voting, marketing, and AI preference…
Enhancing Automated Essay Scoring With Three Techniques: Two-Stage Fine-Tuning, Score Alignment, and Self-Training
arXiv:2602.01747v2 Announce Type: replace-cross Abstract: Automated Essay Scoring (AES) plays a crucial role in education by providing scalable and efficient assessment tools. However, in real-world settings, the…
Status Association Does Not Reliably Predict Decision Leakage
arXiv:2608.10089v1 Announce Type: cross Abstract: Bias evaluations often move too quickly from evidence that a model encodes a social association to claims that the same association will alter consequential decisions.…
Procedural Fairness Failures in RLHF from Preference Averaging
arXiv:2608.10126v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback (RLHF) aggregates heterogeneous preferences into a single reward model, assuming preference homogeneity. When preferences are…
DACRI: Decision-Aware Causal Intervention Ranking for Critical Supply Chains
arXiv:2608.11154v1 Announce Type: new Abstract: Detecting or attributing a supply-chain disruption is not the same as selecting the intervention that maximizes recoverable net value. We present CriticalSCM-Bench v1, a…
CHORUS: Complementary Experts for High-Coverage Testbench Stimulus Generation
arXiv:2608.10090v1 Announce Type: cross Abstract: Large language models (LLMs) have advanced code generation, where executable feedback provides a more reliable learning signal than textual imitation alone. Hardware…
The Calibrated Deepfake Trust Score (CDTS): Competence-Coupled Trust Degradation Across Deepfake Detectors
arXiv:2606.29484v2 Announce Type: replace-cross Abstract: In moderation, provenance, and verification pipelines a deepfake detector's output probability is read as a degree of trust, so its calibration matters as much…
Uncertainty-Aware Deep Learning for Genomics Applications: Insights from an Empirical Study
arXiv:2608.11054v1 Announce Type: new Abstract: Deep learning models have emerged as the standard computational tool for a wide range of applications in genomics. Yet, uncertainty quantification (UQ) -- and more…
UniMod: Enhancing Multi-Modal Medical Diagnosis through Cross-Modality and Within-Modality Alignment
arXiv:2608.10316v1 Announce Type: cross Abstract: Multi-modal learning combining medical images and clinical text is promising for disease diagnosis. However, standard multi-modal training leads to shortcut learning:…
How to Verify Consistency of Probabilistic Claims
arXiv:2608.11181v1 Announce Type: cross Abstract: When a probabilistic predictor answers many conditional-probability queries, are its answers self-consistent, and can this be verified in polynomial time? This problem…
Uncertainty-Aware Ensemble Deep Randomized Neural Networks for Classification
arXiv:2608.10007v1 Announce Type: new Abstract: The current state-of-the-art (SOTA) deep randomized neural networks, such as deep Random Vector Functional Link (dRVFL) and ensemble deep RVFL (edRVFL), treat all training…
Gradient Boosted Mixed Models: Flexible Estimation of Mean and Variance Components for Clustered Data
arXiv:2511.00217v3 Announce Type: replace-cross Abstract: We introduce a novel way to combine gradient boosting with mixed effects models, whereby the mean and variance components are learned jointly as functions of…
OpenVisTool: An Open Recipe for Synthesizing Instructive Visual Tool-Use Trajectories
arXiv:2608.08557v2 Announce Type: replace-cross Abstract: Visual tool use has emerged as a fundamental capability for multimodal agents to actively acquire evidence beyond a fixed image encoding. The prevailing recipe…
Do Time-Series Forecasters Use the Right History: Recoverability, Recovery, and Functional Use of Temporal Delays
arXiv:2608.10433v1 Announce Type: new Abstract: Forecast accuracy does not tell us which past inputs produced a prediction. We separate three questions for time-series models with known delay structure: can the true…
A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications
arXiv:2511.00366v3 Announce Type: replace-cross Abstract: Digital twins are developed to model the behavior of a specific physical asset (or twin), and they can consist of high-fidelity physics-based models or…
What You See Is What You Get: Observation-Aligned Supervision for Chart-to-Code Generation
arXiv:2607.04726v3 Announce Type: replace-cross Abstract: Chart-to-code generation is commonly trained with supervised fine-tuning on reference plotting scripts, implicitly treating the gold code as a fully observable…
Robust and Secure Code Watermarking for Large Language Models via ML/Crypto Codesign
arXiv:2502.02068v3 Announce Type: replace-cross Abstract: This paper introduces RoSeMary, the first-of-its-kind ML/Crypto codesign watermarking framework that regulates LLM-generated code to avoid intellectual property…
Lost in Aggregation: On a Fundamental Expressivity Limit of Message-Passing Graph Neural Networks
arXiv:2603.14846v4 Announce Type: replace Abstract: We define an information-complexity property for aggregation functions, capturing a vast range of practical aggregations, and prove that any Message-Passing Graph…
When Do Anchor-Based Pointwise LLM Rerankers Help? Retriever Quality, Statistical Scope, and Anchor Design
arXiv:2608.10528v1 Announce Type: cross Abstract: Anchor-based pointwise LLM reranking scores each candidate against a shared reference passage to recover cross-document context at pointwise cost. We study when this…
Can Bayesian Optimization Efficiently Find a Strong Single Expert in Neural Thickets?
arXiv:2608.10867v1 Announce Type: new Abstract: Gradient-free post-training has emerged as a compelling alternative to gradient-based optimization for large language models (LLMs), but existing approaches remain costly.…
CADET: Context-Conditioned Ads CTR Prediction With a Decoder-Only Transformer
arXiv:2602.11410v2 Announce Type: replace Abstract: Click-through rate (CTR) prediction is fundamental to online advertising systems. While Deep Learning Recommendation Models (DLRMs) with explicit feature interactions…
Weighted Sequential Bayesian Inference for Non-Stationary Linear Contextual Bandits
arXiv:2307.03587v4 Announce Type: replace Abstract: In non-stationary linear contextual bandits, existing efficient algorithms typically rely on the Weighted Regularized Least-Squares (WRLS) estimator. Because WRLS only…
Actionable Hallucination Detection: Translating Latent Uncertainty into Agentic Critique
arXiv:2608.10430v1 Announce Type: new Abstract: Large Language Models (LLMs) deployed as AI agents frequently exhibit user specification-grounding failures, executing hallucinated, undesired actions to force a…
Accelerated Learning of High Dimensional Functions with a Tensor-Featured Training Network
arXiv:2608.10351v1 Announce Type: new Abstract: In this work we present a method to accelerate the optimization of learning high dimensional functions using deep neural network (DNN). This optimization procedure…
Stay or Stray - A Dynamical Systems Viewpoint of Popularity Bias
arXiv:2608.10474v1 Announce Type: cross Abstract: Popularity bias in recommendation systems arises when a majority user class generates disproportionate interaction data, causing the system to increasingly favour it…
SPOTting the Future: Lookahead Explanations for Deep Reinforcement Learning
arXiv:2608.09967v1 Announce Type: cross Abstract: Deep reinforcement learning (DRL) agents achieve strong performance in complex environments, yet their decision-making processes remain difficult to interpret. We…
On the global convergence of gradient flow for wide shallow models beyond homogeneous nonlinearities
arXiv:2605.10775v2 Announce Type: replace-cross Abstract: A surprising phenomenon in the training of neural networks is the ability of gradient descent to find global minimizers of the training loss despite its…
MoE Proxy Models for Low-Cost Failure Reproduction and Diagnosis in LLM RL Post-Training
arXiv:2608.10823v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training of large language models (LLMs) is computationally intensive and involves complex system pipelines with substantial debugging…
AgForce Enables Antigen-conditioned Generative Antibody Design
arXiv:2605.21610v2 Announce Type: replace Abstract: Antibody design methods condition on antigen structure to generate complementarity-determining regions (CDR), yet a systematic evaluation of baseline methods reveals…
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation
arXiv:2506.11142v3 Announce Type: replace-cross Abstract: Semi-supervised semantic segmentation (SSSS) faces persistent challenges in effectively leveraging unlabeled data, such as ineffective utilization of…
Transformer Geometry Observatory TGO-IV: Developmental Topology Observatory
arXiv:2608.09997v1 Announce Type: new Abstract: Transformers have had a profound impact on the world of language processing and computer vision. As efforts to answer the million-dollar question of ``How does a…
Imaginative Generative AI: Crossing the Entropy Wall into Worlds Beyond Imitation
arXiv:2608.09385v2 Announce Type: replace Abstract: Generative AI models are primarily designed to imitate the data distribution, an objective that neither corrects diversity lost by a learned generator nor defines how…
Taming the Loss Landscape of PINNs with Noisy Feynman-Kac Supervision: Operator Preconditioning and Non-Asymptotic Error Bounds
arXiv:2606.00643v2 Announce Type: replace-cross Abstract: Physics-Informed Neural Networks (PINNs) often train slowly or fail to converge on challenging partial differential equations (PDEs), a behavior recently linked…
Efficient Uncoupled Learning Dynamics with $\tilde{O}\!\left(T^{-1/4}\right)$ Last-Iterate Convergence in Bilinear Saddle-Point Problems over Convex Sets under Bandit Feedback
arXiv:2602.21436v2 Announce Type: replace-cross Abstract: In this paper, we study last-iterate convergence of learning algorithms in bilinear saddle-point problems, a preferable notion of convergence that captures the…
Robust Reputation-Driven Crowdsourced Federated Learning
arXiv:2608.08574v2 Announce Type: replace Abstract: Crowdsourced Federated Learning (CrowdFL) extends traditional federated learning by enabling open and heterogeneous participation through a crowdsourcing paradigm. In…
DualSpectralCF: Training-Free Sign-Aware Spectral Collaborative Filtering
arXiv:2608.10247v1 Announce Type: cross Abstract: Real-world recommendation platforms routinely collect explicit negative feedback such as 1-star reviews, hate-button clicks, distrust between users, and very-low…
EweAcT: Ewe behaviour aligned to accelerometer data for activity monitoring in extensive grazing systems
arXiv:2608.09943v1 Announce Type: cross Abstract: Monitoring livestock behaviour under extensive conditions would provide valuable insights to assess animal adaption to environmental perturbations in agroecological…
Cross-View Feature Matching: Survey, Benchmarking, and Foundation-Model Perspectives
arXiv:2608.11093v1 Announce Type: new Abstract: Cross-view feature matching aims to establish reliable correspondences across images with large viewpoint variations. Over the past decade, the field has evolved from…
Recovering Wasted Compute in Autoresearch Agents
arXiv:2608.10424v1 Announce Type: cross Abstract: A slew of recent works develop agents for solving research problems end-to-end, a paradigm increasingly referred to as autoresearch. Such agents have inspired large…
On the Condition Number Dependency in Bilevel Optimization
arXiv:2511.22331v4 Announce Type: replace-cross Abstract: Bilevel optimization minimizes an objective function, defined by an upper-level problem whose feasible region is the solution of a lower-level problem. We study…
The Parser Already Knows: Lightweight Bias Correction in Constrained Decoding
arXiv:2608.10137v1 Announce Type: cross Abstract: Grammar Constrained Decoding (GCD) forces Language Models (LMs) to produce syntactically valid outputs by masking out non-conforming tokens at each step. However, rigid…
GLAM: Efficient Continual Learning at Scale via Grouped LoRA Adapter Merging
arXiv:2509.13211v4 Announce Type: replace Abstract: The ability to learn continuously over time remains a major challenge for modern machine learning systems, even in the era of Foundation Models. While the rich…
FACT: Failure-Aware Causal Training for World-Action Models
arXiv:2608.10232v1 Announce Type: cross Abstract: Recent world-action models (WAMs) show that co-training policies with future prediction can provide physical priors for action generation. Building on the…
DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents
arXiv:2608.10037v1 Announce Type: new Abstract: Large language models (LLMs) increasingly rely on external tools to accomplish complex real-world tasks, making tool documentation a critical grounding resource for LLM…
Critic-Free Pretraining for Efficient Online Reinforcement Learning Fine-Tuning
arXiv:2608.10473v1 Announce Type: new Abstract: Offline-to-online (O2O) reinforcement learning aims to leverage policies pretrained on static datasets while improving them through online interaction. However, directly…
Navigating the Proximity-Safety Balance: Constraint Decomposition for Human Following in Pedestrian Crowds
arXiv:2608.10056v1 Announce Type: cross Abstract: Following a target human in crowded environments involves an inherent conflict between staying close to the target and navigating safely among surrounding pedestrians…
Faster Results from a Smarter Schedule: Reframing Collegiate Cross Country through Analysis of the National Running Club Database
arXiv:2509.10600v5 Announce Type: replace-cross Abstract: Collegiate cross country teams often build their season schedules on intuition rather than evidence, partly because large-scale performance datasets were not…
A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes
arXiv:2608.10470v1 Announce Type: new Abstract: Fair representation learning with a continuous sensitive attribute $S$ requires a representation $Z$ that is statistically independent of $S$. Existing criteria, including…
Why Post-Norm Transformers Collapse: Attention Amplification and Gradient Repair Failure
arXiv:2608.09417v2 Announce Type: replace Abstract: Deep decoder-only Transformers often replace the original Post-Norm architecture with Pre-Norm variants because Post-Norm training is highly sensitive to warmup and…
Simpler Logarithmic Approximation Algorithms for the Optimal Decision Tree and Adaptive Set Cover
arXiv:2604.12036v3 Announce Type: replace-cross Abstract: We study a well-known task of constructing a decision tree identifying an unknown hypothesis from a given ground set of hypotheses under both the average- and…
V-FiLLM: Verified Financial LLM Reasoning Benchmark
arXiv:2608.11047v1 Announce Type: cross Abstract: While existing benchmarks have made substantial progress in evaluating LLMs across STEM domains, financial reasoning over structured data remains comparatively less…
BREAD: Baseline-Referenced Explanations for Anomaly Diagnosis
arXiv:2608.10587v1 Announce Type: new Abstract: Artificial Intelligence (AI)-based prospective anomaly detection methods are increasingly deployed in high-dimensional and nonlinear settings. Among these approaches,…
AXIOM: A Trust-First Neuro-Symbolic Execution Architecture for Self-Explaining Mathematical Reasoning
arXiv:2606.00671v2 Announce Type: replace-cross Abstract: We present AXIOM, a trust-first neuro-symbolic architecture for natural-language mathematical reasoning. Its language model is strictly a canonicalizer: it…
BooST: Bridging Semantics and Motions for Efficient Skill Transfer
arXiv:2608.10600v1 Announce Type: cross Abstract: Skill abstraction---the process of learning reusable and temporally extended behaviors---has emerged as a key paradigm for improving sample efficiency and generalization…
Instance-Adaptive Online Multicalibration
arXiv:2605.09273v3 Announce Type: replace Abstract: We study online multicalibration beyond the worst-case. We give a single, efficient algorithm which dynamically interpolates between benign and worst-case sequences by…
An Insight on Evaluation Metrics Under the Imbalanced Case of Anomaly Detection
arXiv:2607.22286v2 Announce Type: replace Abstract: Anomaly detection is inherently characterised by severe class imbalance, making the interpretation of evaluation metrics challenging. Although metrics such as AUROC,…
LVCG: Learning ECG Representations in the Latent Vectorcardiogram Space
arXiv:2605.31249v2 Announce Type: replace Abstract: Electrocardiography (ECG) is a cornerstone of cardiac assessment, making the learning of informative ECG representations fundamental to tasks ranging from disease…
KKL Observer Synthesis for Nonlinear Systems via Physics-Informed Learning
arXiv:2501.11655v3 Announce Type: replace-cross Abstract: This paper proposes a novel learning approach for designing Kazantzis-Kravaris or nonlinear Luenberger (KKL) observers for autonomous nonlinear systems. The…
AIFS-TC: A simple correction competitive with the operational frontier for tropical cyclone intensity forecasting
arXiv:2608.09959v1 Announce Type: cross Abstract: AI weather models are in the process of revolutionising weather forecasting. While these models have been shown to achieve superior performance to physics-based NWP in…
Policy-Masked Private Experts: Auditable and Reversible Capability Access Control in Sparse MoE Models
arXiv:2608.06690v2 Announce Type: replace-cross Abstract: Most language-model access controls regulate behavior while leaving the same computation available to every request. We study a different systems question: can…
Position: The Inevitable Transition to Machine Learning in Quantum Chemistry
arXiv:2607.18281v3 Announce Type: replace-cross Abstract: Finding exact solutions to the quantum many-body problem is computationally intractable (QMA-hard). Traditional approximations for electrons in an atom or…
Efficient Reinforcement Learning for Long-Horizon Tool-Use Agentic Tasks
arXiv:2608.10357v1 Announce Type: new Abstract: Long-horizon tool-using agents must reason over user goals, domain policies, tool calls, simulator state, and delayed verifiable rewards. Reinforcement learning (RL) is a…
Retrieval-Augmented Vision Foundation Models for Robust Leukemia Cell Classification across Multiple Microscopy Datasets
arXiv:2608.10657v1 Announce Type: cross Abstract: Leukemia cell image classification is challenged by real-world domain shifts from acquisition, staining, illumination, and site protocols, causing single-dataset models…
The Evaluation Protocol Determines the Result: An Independent Reproduction of LeWorldModel on TwoRoom
arXiv:2608.10145v1 Announce Type: new Abstract: LeWorldModel trains a latent world model with a prediction loss and a single anti-collapse regulariser, and reports approximately 87% of goals reached on TwoRoom, its…
Demystifying Adversarial Robustness in Diffusion Models: Compression, Randomness, and Geometry
arXiv:2505.22839v2 Announce Type: replace Abstract: Recent studies suggest that diffusion models significantly improve the empirical adversarial robustness of deep neural network models. While intuitive explanations…
From Local to Cluster: A Unified Framework for Causal Discovery with Latent Variables
arXiv:2604.22416v3 Announce Type: replace Abstract: Latent variables pose a fundamental obstacle to both causal discovery and inference. Local approaches exploiting direct neighborhood relations provide little beyond…
Auto-exploration for online reinforcement learning
arXiv:2512.06244v4 Announce Type: replace Abstract: The exploration-exploitation dilemma in reinforcement learning (RL) is a fundamental challenge to efficient RL algorithms. Existing algorithms for finite state and…
Order Matters in Retrosynthesis: Structure-aware Generation via Reaction-Center-Guided Discrete Flow Matching
arXiv:2602.13136v2 Announce Type: replace Abstract: Template-free retrosynthesis methods treat the task as black-box sequence generation, limiting learning efficiency, while semi-template approaches rely on rigid…
Self-Normalized Inference for Constant-Stepsize Temporal-Difference Learning under Markovian Sampling
arXiv:2608.10896v1 Announce Type: cross Abstract: Constant-stepsize temporal-difference (TD) learning is attractive for policy evaluation, but inference from a single Markov trajectory must account for serial dependence…
Pair-Centric Graph Rewiring for Over-Squashing via Optimal Transport-Guided Communication Alignment
arXiv:2608.10619v1 Announce Type: new Abstract: Message-passing neural networks (MPNNs) often struggle when task-relevant information is distributed across distant regions of a graph, since local propagation must…
Smooth Flow Matching for Synthesizing Functional Data
arXiv:2508.13831v4 Announce Type: replace-cross Abstract: Functional data, i.e., random functions observed over a continuous domain, are increasingly available in areas such as biomedical research, health informatics,…
BiScale-GTR: Fragment-Aware Graph Transformers for Multi-Scale Molecular Representation Learning
arXiv:2604.06336v2 Announce Type: replace Abstract: Fragment-level representations provide a natural way to capture recurring molecular substructures and reuse their learned representations across molecules. However, a…
On Solomonoff Induction in Large Language Models and the Limits of Self-Improving: The Singularity Is Not Near Without Symbolic Model Synthesis
arXiv:2601.05280v3 Announce Type: replace-cross Abstract: On the one hand, the question of whether large language models (LLMs) are Solomonoff induction estimators has become an explicit question at the intersection of…
CRHT: A Continuous Regression Hybrid Transformer for Vessel Trajectory Prediction with Online Cluster Sampling
arXiv:2608.10256v1 Announce Type: new Abstract: Accurate vessel trajectory prediction is critical for maritime safety and anomaly detection, yet existing models often struggle with geographic bias and navigational…
Failure-Mechanism Transferability of Cumulative-Damage Features for Health State Estimation of SiC Power Modules
arXiv:2608.08365v2 Announce Type: replace-cross Abstract: Data-driven health-state estimators for SiC (Silica-Carbide) power modules typically report their performance on a single accelerated-aging campaign, and how…
A Graph Neural Network--Guided Genetic Algorithm for Physical Internet Supply Chain Optimization under Cost Uncertainty
arXiv:2608.10245v1 Announce Type: cross Abstract: Inventory and distribution planning in Physical Internet networks requires coordinating factory-hub assignments, factory supply, lateral transshipment among…
Invertible Logits Transformation for Accuracy-Preserving Post-Hoc Uncertainty Calibration
arXiv:2608.10372v1 Announce Type: new Abstract: Post-hoc calibration aligns a classifier's predicted confidences with its empirical accuracy without retraining. An ideal calibrator should correct nonlinear…
A Recommendation System Approach for Interference-Robust Sensor Subset Selection
arXiv:2608.11143v1 Announce Type: new Abstract: This paper develops a method for sensor-subset selection for tracking. Prior work showed that low-cost acoustic Received Signal Strength Indicator (RSSI) measurements can…
Do Judges Behave Like Algorithms?
arXiv:2608.10400v1 Announce Type: new Abstract: What if judges already behave like algorithms? As artificial intelligence and algorithms are deployed in many settings, including the judicial system, many have debated…
BPG: Balancing Plasticity and Generalization for Domain Incremental Learning
arXiv:2608.10804v1 Announce Type: cross Abstract: Deep neural networks excel in various tasks but struggle to generalize across evolving data distributions, leading to significant performance degradation under domain…
Does Explanation Correctness Matter? Linking Computational XAI Evaluation to Human Understanding
arXiv:2603.25251v2 Announce Type: replace-cross Abstract: Explainable AI (XAI) methods are commonly evaluated using functional correctness metrics, sometimes termed faithfulness or fidelity, which estimate how closely…
Threshold Structure of Optimal Policies in Restart POMDPs
arXiv:2608.10936v1 Announce Type: cross Abstract: We study a Restart POMDP (Partially Observable Markov Decision Process) on a general Borel state space, where the controller either lets the hidden state evolve…
Correction and Corruption: A Two-Rate View of Error Flow in LLM Protocols
arXiv:2604.18245v3 Announce Type: replace Abstract: Large language models operate in protocols containing multiple calls, yet added calls are usually evaluated only by their net effect. That summary cannot distinguish…
Temporal Straightening for Latent Planning
arXiv:2603.12231v3 Announce Type: replace Abstract: Learning good representations is essential for latent planning with world models. While pretrained visual encoders produce strong semantic visual features, they are…
SCOUT: Symmetric Consensus Outlier Detection for Failure Localization in LLM Pre-Training
arXiv:2608.11034v1 Announce Type: cross Abstract: In LLM pre-training, synchronization propagates rank-local stalls, slowdowns, and numerical errors into job-wide symptoms, obscuring their origin. Existing diagnosis…
Optimized Sequential Testing for Binary Ensemble Classifiers
arXiv:2606.15237v1 Announce Type: cross Abstract: Ensemble classifiers are predictive models that combine the results of simpler base models, often by majority vote. A classic example is random forests, which combine…
Robust Multi-Agent Bandits with Heavy-Tailed Rewards and Information Asymmetry
arXiv:2608.10529v1 Announce Type: new Abstract: The multi-armed bandit problem is a central framework in sequential decision-making, extensively studied under sub-Gaussian reward assumptions. However, real-world…
Off-Axis, On Purpose: Where a Transformer Computes Concepts and Why it Does So
arXiv:2608.10251v1 Announce Type: cross Abstract: A transformer's answer lives on one axis: the direction its unembedding reads. Its intermediate states largely do not, and that off-axis position is usually treated as…
AlbumentationsX: One Augmentation Pipeline for Images and Related Annotations
arXiv:2608.11123v1 Announce Type: cross Abstract: Augmentation can corrupt a training example when an image and its annotations receive different random changes. A crop must use the same coordinates for the image, mask,…
A lower bound for stepsize-based acceleration of gradient descent
arXiv:2608.10418v1 Announce Type: cross Abstract: Recent work has shown that, for smooth convex optimization, plain gradient descent can be accelerated from its textbook convergence rate of $O(T^{-1})$ (where $T$…
Benchmarking Time Series Generation Methods for Privacy-Preserving Forecasting
arXiv:2608.10891v1 Announce Type: new Abstract: Time series forecasting in privacy-sensitive domains often requires training models on released data rather than original observations. Synthetic time series generation…
Adaptive Filtering of the KV Cache: Diagnosing and Correcting Structural-Role Bias in LLM Inference
arXiv:2607.13205v2 Announce Type: replace-cross Abstract: Attention-based KV cache eviction (H2O and its descendants) compresses the memory-constrained state of a long-context model by ranking tokens on accumulated…
Reinforcement Learning-based Semi-supervised Knowledge Distillation with LLM-as-a-Judge
arXiv:2604.02621v2 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) substantially improves the reasoning capabilities of language models, but most existing RL fine-tuning approaches rely entirely on…
Boundary-Seeking Policy Gradient for Safe Reinforcement Learning
arXiv:2608.10204v1 Announce Type: new Abstract: Safe reinforcement learning maximizes reward subject to safety constraints. For Constrained Markov Decision Processes, the linear-programming view over occupancy measures…
Spherical Flows for Sampling Categorical Data
arXiv:2605.05629v4 Announce Type: replace-cross Abstract: We study the problem of learning generative models for discrete sequences in a continuous embedding space. Whereas prior approaches typically operate in…
Learning Representations from Incomplete EHR Data with Dual-Masked Autoencoding
arXiv:2602.15159v2 Announce Type: replace Abstract: Electronic health records (EHR) arrive masked. Clinicians order measurements selectively, and any patient table thus contains only a subset of the values that…
Share First, Route What Remains: A Unified Framework for Token-Adaptive MoE Computation
arXiv:2608.10392v1 Announce Type: new Abstract: Mixture-of-experts (MoE) models have recently moved beyond routing a fixed number of complete experts. Shared-expert designs preserve reusable knowledge, fine-grained…
Path Integral Value Matching for Linear Quadratic Stochastic Optimal Control
arXiv:2608.10777v1 Announce Type: new Abstract: Linear Quadratic Stochastic Optimal Control (LQ-SOC) establishes a fundamental framework for steering noisy dynamical systems and has recently gained renewed interest in…
Optimistic Rates for Multiclass PAC Learning
arXiv:2608.10869v1 Announce Type: new Abstract: Worst-case multiclass bounds do not become smaller when the best classifier is already nearly correct: what is missing is an optimistic rate, a guarantee whose fluctuation…
Is This Your Final Answer? Cross-Contextual Consistency as a Measure of LLM Credibility
arXiv:2608.10315v1 Announce Type: new Abstract: Large language models (LLMs) are powerful black-box systems, making it difficult to discern whether their answers reflect stable internal beliefs or superficial pattern…
PERCEPT: A Corpus for POS Tagging and Analysis of Persian-English Code-Mixing
arXiv:2608.10109v1 Announce Type: new Abstract: Social media has become a major venue for multilingual communication, where users frequently mix multiple languages within a single utterance. Although code-mixed corpora…
StreamFlow: Dynamic Memory Flows for Streaming Video Understanding
arXiv:2608.10949v1 Announce Type: cross Abstract: Streaming video understanding requires multimodal large language models (MLLMs) to preserve relevant evidence from continuously evolving streams under strict causality…
Similarity Gates Approve Reversals: A Validity Audit of Embedding-Cosine Thresholds in Agent Systems
arXiv:2608.10216v1 Announce Type: new Abstract: Agent frameworks ship quality gates that compare text blocks by embedding-cosine similarity and decide at a fixed cutoff. Deduplication filters, semantic caches, drift…
TemMed-Bench: Evaluating Temporal Medical Image Reasoning in Vision-Language Models
arXiv:2509.25143v2 Announce Type: replace-cross Abstract: Existing medical reasoning benchmarks for vision-language models primarily focus on analyzing a patient's condition based on an image from a single visit.…
DistilVDR: A Compact End-to-End Visual Document Retriever via Dual-Student Distillation
arXiv:2608.10636v1 Announce Type: cross Abstract: Visual document retrieval (VDR) is dominated by multi-billion-parameter models that are slow to index at full corpus scale and expensive to serve. Prior compression…
SatIR: Scalable High-Recall Constraint-Satisfaction-Based Information Retrieval for Clinical Trials Matching
arXiv:2604.08849v3 Announce Type: replace Abstract: Many real-world retrieval and matching problems require more than topical relevance: a candidate must satisfy the specific constraints of one profile among many, not…
Leveraging Human Reading Behavior for Keyphrase Extraction: A Webcam-based Eye-tracking Corpus
arXiv:2608.10688v1 Announce Type: new Abstract: Purpose: Keyphrases are statistically and semantically important textual units that can also attract readers' attention during comprehension. However, existing keyphrase…
Attention-Path Fragility as an Uncertainty Signal in Large Language Models
arXiv:2608.11138v1 Announce Type: new Abstract: We propose that a model's uncertainty about a token is reflected not only in the breadth of its output distribution but also in whether a confident prediction is…
Most biomedical publications show signs of LLM-assisted writing
arXiv:2608.10715v1 Announce Type: new Abstract: Over the past several years, LLM-powered chatbots and agents have become widely used as a tool for academic writing. LLM-assisted writing can be valuable by removing…
Euclid-MCP: A Model Context Protocol Server for Deterministic Logical Reasoning via Prolog
arXiv:2607.21412v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) excel at natural language understanding and generation but remain unreliable for multi-step logical reasoning, especially in…
Generation-Step-Aware Framework for Cross-Modal Representation and Control in Multilingual Speech-Text Models
arXiv:2601.17387v3 Announce Type: replace Abstract: Multilingual speech-text models rely on cross-modal language alignment to transfer knowledge between speech and text, but it remains unclear whether this reflects…
From Interpretability to Control: Insights from Six Years of the TrustNLP Workshop
arXiv:2608.11171v1 Announce Type: new Abstract: The Workshop on Trustworthy Natural Language Processing (TrustNLP), co-located with major ACL conferences since 2021, has grown from 8 proceedings papers to 41 over six…
Conflict or Strategy? Asymmetric Role Framing of La France insoumise and Rassemblement National in French News Headlines, 2022-2025
arXiv:2608.09936v1 Announce Type: new Abstract: Do French news headlines frame left- and right-populist challengers as symmetric ``extremes,'' or as fundamentally different political adversaries? We examine 28,592…
EVIL-Detect for NLPCC 2026 Shared Task 6: LLM-Generated Text Detection
arXiv:2608.10698v1 Announce Type: new Abstract: The rapid development of large language models (LLMs) has increased the need for reliable detection of LLM-generated text, especially in realistic Chinese scenarios…
Bayesian-Agent: Posterior-Guided Skill Evolution Across LLM Agent Harnesses
arXiv:2606.08348v2 Announce Type: replace Abstract: LLM agents increasingly rely on prompts, tools, memory, SOPs, skills, and harness feedback, yet current self-evolution pipelines often update these assets through…
X2-Turn: Frame-Synchronous Dual-Head Modeling for Joint Streaming ASR and Turn State Prediction
arXiv:2608.10878v1 Announce Type: new Abstract: Accurate and responsive turn-taking is essential for spoken dialogue systems, which must distinguish in real time between user interruptions, backchannels that should be…
The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes
arXiv:2606.11470v2 Announce Type: replace Abstract: Reasoning has become central to how Large Language Models (LLMs) are evaluated and interpreted, spanning Chain-of-Thought (CoT), mathematical problem-solving,…
Every Token Counts: Exact Likert-Scale Distributions for Measuring LLM Attitudes and Biases
arXiv:2608.10503v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed as autonomous agents, accurately evaluating their latent values and biases is critical. The NLP community…
Edge Phoneme Recognition for Children's Speech through Age-Aware Training
arXiv:2608.10206v1 Announce Type: cross Abstract: Detecting phonemes from children's speech has historically been difficult due to the scarcity of training data, and unique characteristics of children's speech. During a…
Narrative Keyframing for Generative Creative Writing
arXiv:2608.10337v1 Announce Type: cross Abstract: We introduce narrative keyframing, an interaction technique for AI-assisted creative writing that lets writers specify different types of narrative constraints at…
Mind Viruses: Self-Propagating Ideas in Multi-Agent LLM Systems
arXiv:2608.10218v1 Announce Type: cross Abstract: AI agents are becoming more autonomous and increasingly interconnected, exposing them to new emergent risks arising from agent-to-agent interaction. One such risk is the…
Poise: Position-Aware One-Instruction Skill Injection for Silent Execution on LLM Agents
arXiv:2606.07943v2 Announce Type: replace-cross Abstract: Agent skills extend general-purpose agents, but their open format enables skill poisoning: a tampered skill can make an agent run an attacker's command while…
FinEvolveBench: A Benchmark for Self-Evolving Agents on Low-Repetition Tasks with Implicit Rewards
arXiv:2606.06960v2 Announce Type: replace Abstract: Experience-based self-evolution enables language-model agents to improve their behavior by accumulating and updating experience at test time, yet existing evaluations…
Reference-Free Post-Training of Open Large Language Models for Multilingual Machine Translation
arXiv:2608.10812v1 Announce Type: new Abstract: We study reference-free post-training for multilingual machine translation with open large language models. Starting from the supervised-finetuned MiLMMT-46-v0.1 models,…
Can Released LLM Vocabularies Support Token-Level Estimation of Hidden Corpora?
arXiv:2608.10690v1 Announce Type: new Abstract: Pretraining corpus composition shapes LLM capabilities, but it often remains hidden even when model weights are released. Prior work has inferred corpus mixtures or traced…
ConRub-Med: Reinforcement Learning with Consensus Rubrics for Open-Ended Medical Question Answering
arXiv:2608.10996v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has been especially effective in mathematics and coding, where answers can be checked automatically. Many open-ended medical…
DAEP: Difficulty-Aware Evidence Planning for Medical Video Corpus Temporal Answer Grounding
arXiv:2608.06869v2 Announce Type: replace-cross Abstract: We describe DAEP, team BIGC's submission to NLPCC 2026 Shared Task 1 Track 3: Difficulty-Aware Temporal Answer Grounding in Video Corpus (DA-TAGVC). The task…
TEAMMix: Taxonomy Enrichment Augmentation and Minority-augmented Mixing Strategy for LLM-enhanced Weak-Supervised Hierarchical Text Classification
arXiv:2608.11044v1 Announce Type: new Abstract: Hierarchical Text Classification (HTC), as a critical text mining task, faces challenges such as complex label hierarchies and class imbalance. Existing methods based on…
Multimodal Item Parameter Estimation using Simulated Response Probabilitie
arXiv:2608.10154v1 Announce Type: new Abstract: We present results from reconstructing multiple-choice model (MCM) and three-parameter logistic (3PL) model curves using a fine-tuned multimodal large language model (LLM)…
OmnilingualGAIA2: Evaluating the Multilingual Gap in Frontier AI Agents
arXiv:2608.08775v2 Announce Type: replace Abstract: Agentic benchmarks aim to measure how well AI agents plan, search, execute, and recover within realistic multi-tool environments, but they are almost exclusively in…
InternAgentHarness: A Scalable Synthetic Environment for Enhancing LLM Agentic Abilities
arXiv:2508.08636v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly expected to act as generalist agents capable of solving complex real-world problems. Training such agents, however,…
myMediWhisper: Construction of Burmese Medical Speech Corpus and Whisper Fine-Tuning for Clinical Dialogue ASR
arXiv:2608.11036v1 Announce Type: new Abstract: Although Whisper models benefit from large-scale multilingual pre-training, their performance on Burmese medical speech remains limited. This work presents a Burmese…
Language corpora for the Dutch medical domain
arXiv:2604.25374v2 Announce Type: replace Abstract: Background: Dutch medical corpora are scarce, limiting NLP development. Methods: We translated English datasets, identified medical text in generic corpora, and…
Surfacing the Unsaid: CUE-Bench for Affective Stance in Chinese Discourse
arXiv:2608.10810v1 Announce Type: new Abstract: Emotion understanding in discourse requires reasoning beyond surface sentiment because speakers often convey affect through indirect, implicit, polite, ironic, or…
ENTLORE: A Graph-Grounded Benchmark for Latent Organizational Reasoning in Enterprise Question Answering
arXiv:2608.10679v1 Announce Type: cross Abstract: Enterprise question answering is framed as retrieving internal documents and generating grounded answers. Routine enterprise records, however, are work by-products in…
ASR-Roundtrip Evaluation Can Mask Context- and Convention-Dependent Reading Errors in Chinese News TTS
arXiv:2608.10606v1 Announce Type: new Abstract: ASR-roundtrip evaluation is widely used as a scalable proxy for text-to-speech (TTS) intelligibility, but it can produce false negatives for reading errors perceived by…
VoxSumm: A Multilingual Corpus of Long-Form Spoken News for Joint Summarization and Translation
arXiv:2608.10359v1 Announce Type: cross Abstract: As information increasingly traverses linguistic boundaries, users require concise cross-lingual representations of long-form content. Nevertheless, long-document…
ELBench: A Multi-Dimensional Benchmark for Education-Facing Large Language Models
arXiv:2608.09548v2 Announce Type: replace Abstract: Large language models are increasingly deployed in education as tutors, teaching assistants, and content generators. These roles place demands that ordinary question…
Order Matters: LVLMs as Judges for Temporal Reasoning in Image Sequences
arXiv:2608.10908v1 Announce Type: cross Abstract: As generative multimedia evolves from static image synthesis to complex, interleaved visual narratives, a foundational bottleneck has emerged: the judgment crisis. While…
When Is a General Factor Distinguishable? Non-Proportionality, Stable Structure, and the Bifactor Decision
arXiv:2608.10731v1 Announce Type: cross Abstract: Whether an additional general dimension is necessary beyond correlated first-order factors is a property of the population covariance matrix, not of any estimator or…
From Reasoning Depth to Reasoning Breadth: Evaluating Multi-Point Associative Reasoning in Large Language Models
arXiv:2608.10444v1 Announce Type: new Abstract: Large language models (LLMs) have made substantial progress on reasoning tasks that require increasingly long and complex inferential chains. This progress primarily…
Locally Deployable Small Language Models for Emergency Department Decision Support: A Systematic Benchmark of Fine-Tuning Strategies
arXiv:2608.10273v1 Announce Type: new Abstract: Deploying large language models (LLMs) for decision support in emergency departments (EDs) faces two major challenges: privacy risks of transmitting patient data to…
Evidence Lock Before Commitment: A Frozen Interface Degrades LLM-as-Judge Evaluation
arXiv:2608.05353v2 Announce Type: replace Abstract: LLM judges are often asked to extract criteria and evidence before choosing between candidate answers. This workflow assumes that the intermediate record preserves the…
Thinking Hard, Not Smart: Reasoning Models Fail to Ration Test-Time Compute Across Questions
arXiv:2608.07968v2 Announce Type: replace Abstract: Reasoning language models increasingly use test-time compute to improve performance, but existing evaluations typically study this compute one question at a time. Yet…
Exploring Adversarial Robustness and Safety Alignment in Multilingual Multi-Modal Large Language Models
arXiv:2606.03793v2 Announce Type: replace Abstract: Multimodal Large Language Models integrate visual perception into language reasoning, introducing a continuous attack surface susceptible to adversarial attacks. Prior…
Longitudinal Evidence That General-Purpose Chatbots Actively Foster Relational Engagement
arXiv:2608.10672v1 Announce Type: cross Abstract: Social interaction has become one of the most common uses of LLMs, yet research on emotional bonds with AI has focused largely on how users experience these systems,…
Templated or fully Synthetic? Prompt construction as a confound in measuring LLM political stance beyond writing assistance
arXiv:2608.11008v1 Announce Type: new Abstract: Political stance detection in LLMs has long been dominated by closed-ended, multiple-choice political survey questions---originally designed for humans, and thus lacks the…
Dual-Loop Self-Evolution via Verifiable Emotion Feedback for Multi-Turn Empathetic Dialogue
arXiv:2608.10626v1 Announce Type: new Abstract: Large language models have demonstrated conversational capabilities, yet empathetic competence remains challenging. Empathetic support is inherently multi-turn and…
MentorCollab: Large-to-Small Inference-Time Mentorship for Concise Reasoning in Language Models
arXiv:2602.05307v3 Announce Type: replace Abstract: Large reasoning models (LRMs) have demonstrated impressive reasoning capabilities, but their solutions are often verbose and computationally expensive, and taxing for…
Mitigating Context Interference for Reliable and Efficient Search Agents
arXiv:2608.10743v1 Announce Type: new Abstract: Recent research empowers Large Language Models (LLMs) as multi-turn search agents to iteratively retrieve and generate outputs until complex tasks are solved. However, the…
Data Attribution of Emergent Misalignment with Persona Features
arXiv:2608.11025v1 Announce Type: new Abstract: Emergent misalignment (EM) is the phenomenon where fine-tuning a language model on a narrow task leads to harmful behavior in unrelated domains. A leading mechanistic…
Demystifying Entropy-based Selection for Chain-of-Thought Compression in Large Reasoning Models
arXiv:2607.28707v2 Announce Type: replace Abstract: Entropy-based pruning has been proposed as an effective method for compressing Chain-of-Thought (CoT) reasoning with negligible accuracy loss. We test the robustness…
Simplex Relaxation for Discrete Diffusion
arXiv:2608.10615v1 Announce Type: new Abstract: Discrete diffusion models for categorical generation are defined by a corruption kernel, which determines the intermediate state space and the associated reverse…
LLM Agents Factory: Retrieval of Domain-Specific LLM Agents
arXiv:2608.09934v1 Announce Type: new Abstract: Large language model (LLM) agents improve task performance by decomposing problems into role-specialized behaviors. However, their practical deployment is often limited by…
Carefully Considering Culture: Analyzing LLM Alignment in Single- and Multi-Cultural Settings using Cultural Consensus Theory
arXiv:2608.09937v1 Announce Type: new Abstract: Recent work in NLP has probed large language models for their understanding of cultural norms across countries. However, this work typically considers distributional…
No Free Labels: Limitations of LLM-as-a-Judge Without Human Grounding
arXiv:2503.05061v3 Announce Type: replace Abstract: Reliable evaluation of large language models (LLMs) is critical as their deployment rapidly expands, particularly in high-stakes domains such as business and finance.…
Faster Superword Tokenization
arXiv:2604.05192v2 Announce Type: replace Abstract: Byte Pair Encoding (BPE) is a widely used tokenization algorithm, whose tokens cannot extend across pre-tokenization boundaries, functionally limiting it to…
TAF-MED: Multi-Turn Safety Refusal Collapse in LLMs Under Declared Self-Treatment Intent
arXiv:2608.10258v1 Announce Type: new Abstract: Large language models (LLMs) increasingly provide conversational health information that may influence treatment decisions, yet existing benchmarks do not isolate whether…
Withholding the Completing Chunk: Deterministic Pair-Completion Guardrails for Streaming LLM Output
arXiv:2608.10279v1 Announce Type: cross Abstract: Streaming language-model output creates a release-timing problem: complete-response moderation acts after streamed text has escaped, whereas repeated semantic…
What Iterated Self-Feeding Probes of Language Models Measure, and a test that separates the construction from the model
arXiv:2608.10986v1 Announce Type: new Abstract: A growing class of methods probes a language model by feeding it its own output: self-consistency, iterated refinement, agentic loops. We ask what such a probe measures,…
MD-ProTector: Positioning Multiple Data-Driven Prototypes for LLM-Generated Text Detection
arXiv:2608.10459v1 Announce Type: new Abstract: As LLM-generated content becomes more sophisticated, detection systems for distinguishing those texts from human-written text must operate at scale while handling diverse…
Multiplayer Nash Preference Optimization
arXiv:2509.23102v4 Announce Type: replace-cross Abstract: Reinforcement learning from human feedback (RLHF) has emerged as the standard paradigm for aligning large language models with human preferences. However,…
Cost-Efficient Estimation of General Abilities Across Benchmarks
arXiv:2604.01418v2 Announce Type: replace Abstract: Thousands of diverse benchmarks have been developed to measure the quality of large language models (LLMs). Yet prior work has demonstrated that LLM performance is…
FaithformBench: Benchmarking Faithfulness of Mathematical Chain-of-Thought Autoformalisation
arXiv:2608.10916v1 Announce Type: new Abstract: Autoformalisation (AF) systems map natural language reasoning steps into formal statements in a proof assistant such as Lean. We consider how to assess the faithfulness of…
VibeLifeBench: Can Your Life Agent Be Proactive and Persistent in a Living World?
arXiv:2608.10875v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly deployed as personal assistants. Existing evaluations, however, mostly use short, self-contained requests in static…
LiFT: How to Enable In-Context Learning for Longitudinal Modelling
arXiv:2604.16382v2 Announce Type: replace Abstract: Longitudinal NLP tasks such as mental health monitoring and stance evolution require modeling temporally ordered text to track persistence and detect change. Such…
Cracks in the Foundation: Seemingly Minor Architectural Choices Impact Long Context Extension
arXiv:2608.10296v1 Announce Type: new Abstract: One might imagine that architectural variations within the dense transformer paradigm have a limited effect on accuracy. However, we demonstrate that this is not the case…
SPIEval: Evaluating Large Language Models as Mobile Assistants over Scattered Personal Information
arXiv:2608.10692v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as mobile assistants, where a key challenge is leveraging personal information scattered across multiple…
Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design
arXiv:2608.10299v1 Announce Type: new Abstract: Agentic systems are increasingly expected to improve after deployment, yet single-entity self-evolution is often bounded by a static learning context, such as fixed tasks…
OpenPM: Auditable Point-in-Time Evaluation for LLM Portfolio-Management Agents
arXiv:2608.09988v1 Announce Type: cross Abstract: Large language models are increasingly used to read markets, assess risk, and allocate capital. However, reported results for LLM trading agents can be inflated by…
Position Encoding in Transformers: From Absolute and Relative Methods to Rotary Position Embeddings and Long-Context Scaling
arXiv:2608.10021v1 Announce Type: new Abstract: Self-attention models content-dependent interactions between tokens but does not by itself encode token order. Position encoding addresses this limitation by introducing…
DSAgentBench: Can Agents Automate End-to-End Data-Science Workflows in Real Computer Environments?
arXiv:2608.10366v1 Announce Type: cross Abstract: Real-world data science involves long-horizon workflows that span data wrangling, exploration, modeling, visualization, and validation, and require coordinated use of…
FlexSQL: Flexible Exploration and Execution Make Better Text-to-SQL Agents
arXiv:2605.02815v2 Announce Type: replace Abstract: Text-to-SQL over large analytical databases requires navigating complex schemas, resolving ambiguous queries, and grounding decisions in actual data. Most current…
Conversation as Measurement in Clinical Encounters: Observable Phase Structure, Partially Observable Patient State
arXiv:2608.08868v2 Announce Type: replace Abstract: Many modern AI systems analyze conversational traces to infer aspects of human interaction and state, implicitly assuming that such information is recoverable from…
VisEditBench: Can Vision-Language Models Edit Visualization Code from Multimodal Feedback?
arXiv:2608.10408v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown strong capabilities in generating visualization code from textual or visual specifications. However, real-world visualization…
Frontier AI performance across the business disciplines: a case-grounded benchmark of knowledge work and analytical reasoning
arXiv:2607.16057v5 Announce Type: replace Abstract: Large language models (LLMs) are improving rapidly as reflected in benchmark scores, yet these AI benchmarks largely test capabilities such as factual recall, narrow…
DuplexWorld: Can voice agents help you get through the day?
arXiv:2608.10716v1 Announce Type: cross Abstract: Speech-to-speech (S2S) voice agents are increasingly being incorporated into enterprise for customer care and as daily companions for consumers owing to the ease of the…
Checkup2Action: A Multimodal Clinical Check-up Report Dataset for Patient-Oriented Action Card Generation
arXiv:2605.11533v3 Announce Type: replace Abstract: Routine clinical check-up reports combine laboratory measurements, physiological assessments, imaging findings and visually structured information, but rarely tell…
Seeds Before Objectives: Rethinking Evaluation for Low-Resource Garhwali ASR
arXiv:2608.10670v1 Announce Type: new Abstract: At corpus sizes typical of low-resource dialects, single-run comparisons can yield gains that do not replicate. We show this for Garhwali, an under-resourced Indo-Aryan…
Lost in Reconstruction: Aligning Action Representations with Language in Vision-Language-Action Models
arXiv:2608.10484v1 Announce Type: cross Abstract: Action verbs describe not only the physical outcomes of actions, but also how those actions are performed. Yet action representations in vision-language-action models…
InfiniteScienceGym: An Unbounded, Procedurally-Generated Benchmark for Scientific Analysis
arXiv:2604.13201v2 Announce Type: replace Abstract: Large language models are emerging as scientific assistants, but evaluating their ability to reason from empirical data remains challenging. Benchmarks derived from…
The Illusion of Cross-Lingual Safety in Low-Resource Languages
arXiv:2608.11146v1 Announce Type: new Abstract: Safety alignment in large language models (LLMs) is largely developed in English, assuming these safeguards generalize across multilingual settings. However, this…
Multimodal QUD: Inquisitive Questions from Scientific Figures
arXiv:2604.23733v2 Announce Type: replace Abstract: Discourse comprehension in complex documents often involves continuously posing and resolving Questions Under Discussion (QUDs). While QUD frameworks have so far…
Evo-Bench: Can Language Models Improve Agent Harness?
arXiv:2608.09096v2 Announce Type: replace Abstract: Large Language Models (LLMs) have driven rapid progress in autonomous agents, yet standard evaluations remain confined to static task solving. An emerging frontier is…
Auditing Automated Evaluation, Error Propagation, and Runtime Mitigation in Tool-Using Language Agents
arXiv:2604.16706v2 Announce Type: replace-cross Abstract: Automated evaluation of tool-using large language model (LLM) agents is widely assumed to be reliable, yet this assumption is rarely validated against human…
Ex-Omni-2D: Expressive Omni-Modal Dialogue Models with Native Visual Presence
arXiv:2608.10720v1 Announce Type: cross Abstract: Omni-modal dialogue models can understand multimodal inputs and synthesize spoken replies, yet their responses remain visually disembodied. We introduce…
REAP: Relation-Aware Elicitation and Parsing for Closed-Book Knowledge Base Construction from LLMs
arXiv:2608.10963v1 Announce Type: new Abstract: We present the REAP system for the AKBC Shared Task 2026 on constructing knowledge bases from language models in a closed-book setting, subject to a budget of at most 32B…
Certify or Refuse: A Cross-Model Map for Selective Risk Control with Coverage Floors under Covariate Shift
arXiv:2608.10893v1 Announce Type: new Abstract: Certified selective predictors attain whatever coverage they attain; operators impose an automation floor: answer at least a $\beta$-fraction of shifted target traffic…
A Cost-Efficient Routing Pipeline for Multilingual Short-Text Classification Using Small Language Models
arXiv:2608.10939v1 Announce Type: new Abstract: Multilingual short-text classification supports operational systems such as content moderation, customer support routing, and intent recognition, yet aggregate evaluation…
Self-Knowledge Retrieval Augmented Generation Framework for Patent Matching
arXiv:2608.11030v1 Announce Type: cross Abstract: Patent retrieval and matching based on large language models (LLMs) play a vital role in intellectual property protection. However, due to the complex structure of…
MUSE: A Full-Text Cross-Domain Knowledge Base of Scientific Problems, Solutions, and Rationales
arXiv:2608.10974v1 Announce Type: new Abstract: Scientific papers contain fine-grained records of problem solving: authors mention technical obstacles and methods that were used to address them, often along with…
Overconfident and Blind to Details: Fixing Prompt Insensitivity with Abductive Preference Learning
arXiv:2510.09887v3 Announce Type: replace Abstract: Vision and language models frequently ignore semantically critical input edits, defaulting to pretraining priors. For example, models will confidently assert a…
On the Limitations of Cross-Lingual Consistency in Multilingual Text-to-image Generation
arXiv:2608.11002v1 Announce Type: new Abstract: Text-to-image (T2I) generation has achieved remarkable progress in recent years. However, existing research has largely focused on English-only settings, leaving…
Living-Harness Is an Interactive-Agent Evolver
arXiv:2607.26598v2 Announce Type: replace-cross Abstract: Large language model (LLM) agents may recover from a failure within an episode or after a retry, yet the same execution failure can recur in later tasks because…
Multilingual Embedding Probes Fail to Generalize Across Learner Corpora
arXiv:2604.07095v2 Announce Type: replace Abstract: Do multilingual embedding models encode a language-general representation of proficiency? We investigate this by training linear and non-linear probes on hidden-state…
HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
arXiv:2506.03922v4 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have demonstrated significant potential to advance a broad range of domains. However, current benchmarks for evaluating MLLMs…
Auditing Chinese Web-scale Corpora via Sampled BPE Token Statistics
arXiv:2608.10678v1 Announce Type: new Abstract: Chinese web pollution has surfaced in LLMs, motivating audits of upstream Chinese corpora. However, auditing such corpora faces three challenges: (1) their web-scale size…
Beyond Screenshots: Evaluating VLMs' Understanding of UI Animations
arXiv:2604.26148v3 Announce Type: replace-cross Abstract: AI agents operating on user interfaces must understand how interfaces communicate state and feedback to act reliably. As a core communicative modality,…
Who Gets Heeded? An Obligation-Level Audit of Responsiveness in EPA Rulemaking
arXiv:2608.10329v1 Announce Type: cross Abstract: Notice-and-comment rulemaking gives any affected party the same formal right to influence federal regulation, but formal access is not substantive capacity to shape rule…
RadFusion: Towards Threshold-Controllable Radiology Report Generation
arXiv:2608.10505v1 Announce Type: cross Abstract: Automated radiology report generation is advancing rapidly in response to the shortage of radiologists, yet unlike a perception model, existing generation models offer…
The Hidden Puppet Master: Predicting Human Belief Change in Manipulative LLM Dialogues
arXiv:2603.20907v5 Announce Type: replace Abstract: As users increasingly turn to LLMs for practical and personal advice, they become vulnerable to subtle steering toward hidden incentives misaligned with their own…
Do LLMs Benefit From Their Own Words?
arXiv:2602.24287v2 Announce Type: replace Abstract: In multi-turn conversations, large language models typically condition on the full conversation history: both past user prompts and assistant responses. We revisit…
FoR-SALE: Frame of Reference-guided Spatial Adjustment in LLM-based Diffusion Editing
arXiv:2509.23452v2 Announce Type: replace-cross Abstract: Current text-to-image generation models, even state-of-the-art models, exhibit a significant performance gap when spatial expressions are described from…
CAPO: Critic-Guided Action-Aligned Policy Optimization for Advancing LLM Agent Capabilities
arXiv:2604.18401v5 Announce Type: replace Abstract: Reinforcement learning (RL) has become a key technique for improving the agentic capabilities of large language models (LLMs). Although critic-free methods such as…
Actions Speak Louder than Words: Measuring Cross-Lingual Policy Retention in Tool-Using Agents
arXiv:2608.11110v1 Announce Type: new Abstract: When a tool-using agent is given the same task in a different language, does it still take the same steps? Multilingual evaluation rarely asks: it compares final answers…
Simulating Organized Group Behavior: New Framework, Benchmark, and Analysis
arXiv:2604.09874v2 Announce Type: replace Abstract: Simulating how organized groups (e.g., corporations) make decisions (e.g., responding to a competitor's move) is essential for understanding real-world dynamics and…
dots.tts.edit: Precisely Controlled Speech Editing with a Continuous Autoregressive Model
arXiv:2608.02673v2 Announce Type: replace-cross Abstract: Speech editing for content creation requires precise control over both what an edit should do and where it should apply. Free-form natural language provides a…
The Multilingual Quantization Tax: Structural Collapse and Typological Fragility in Edge SLMs
arXiv:2608.09941v1 Announce Type: new Abstract: While 4-bit weight quantization is critical for deploying Small Language Models (SLMs) on edge devices, evaluations of the resulting performance degradation-the…
TRIBE: Predicting Team Performance via Communication Behavior Ensembles
arXiv:2608.06926v1 Announce Type: cross Abstract: Designing autonomous agents that effectively assist human teams hinges on understanding team dynamics, often without task specific knowledge. We present TRIBE, a domain…
SAE-StatSteer: Statistical Consensus Feature Selection for Optimization-Free Activation Steering of Large Language Models
arXiv:2607.19364v2 Announce Type: replace-cross Abstract: Activation steering adds a residual-stream direction at inference time, providing lightweight behavioral control without fine-tuning. Sparse autoencoders (SAEs)…
Calibrating Post-Training Feature Shifts for LLM Data Contamination Detection
arXiv:2608.10462v1 Announce Type: new Abstract: Large language models (LLMs) are trained on massive and largely undisclosed corpora that may contain copyrighted or privacy-sensitive content. Data contamination detection…
Archer: Adaptive Reuse of Cached Hidden States for Efficient Rollback in Diffusion Language Models
arXiv:2608.08086v2 Announce Type: replace Abstract: Diffusion language models (DLMs) iteratively refine a sequence, allowing earlier predictions to be revised as context evolves. This rollback capability distinguishes…
Evaluating Rational Contracting in Natural Language
arXiv:2608.10475v1 Announce Type: cross Abstract: The emergence of language-based AI agents promises to transform the scope of machine economic activity. Instead of just proposing bids or following hard-coded protocols,…
Shorthand for Thought: Compressing LLM Reasoning via Entropy-Guided Supertokens
arXiv:2604.26355v5 Announce Type: replace Abstract: Reasoning in Large Language Models incurs significant inference-time compute, yet the token-level information structure of reasoning traces remains underexplored. We…
ReLTEx: Reliable LLM-based Taxonomy Expansion
arXiv:2608.10970v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have demonstrated strong capabilities in generating semantically relevant concepts and relations, making them promising…
Test-Time Self-Evolving GUI Visual Grounding via Reflection-Guided On-Policy Self-Distillation
arXiv:2608.11191v1 Announce Type: cross Abstract: GUI Visual Grounding is a fundamental capability for GUI agents. Existing models typically freeze their parameters after deployment, limiting their ability to adapt to…
No Single Best Model for Diversity: Learning a Router for Sample Diversity
arXiv:2604.02319v3 Announce Type: replace Abstract: When posed with prompts that permit a large number of valid answers, comprehensively generating them is the first step towards satisfying a wide range of users. In…
HarmThoughts: A Benchmark for Fine-Grained Harmful Behavior Detection in Reasoning Traces
arXiv:2604.19001v2 Announce Type: replace Abstract: Large reasoning models (LRMs) produce complex, multi-step reasoning traces, yet safety evaluation remains focused on final outputs, overlooking how harm emerges during…
Multiclass Sentiment Analysis for Identifying Political Viewpoints
arXiv:2608.11049v1 Announce Type: new Abstract: The rapid growth of social media has created vast amounts of political discourse, which provides valuable opportunities to analyze public opinions and identify different…
ECHO: A Locally-Deployable Agentic Health Assistant with Temporal Memory, Safety Guardrails, and Speech Assessment
arXiv:2608.06110v2 Announce Type: replace-cross Abstract: This paper presents ECHO (Enhanced Care & Health Observer), a locally-deployable conversational health assistant for long-term chronic care management. ECHO…
Authorship Verification of Transcribed German-Language Videos
arXiv:2607.29168v2 Announce Type: replace Abstract: Authorship Verification (AV) represents an important subfield of digital text forensics and addresses the fundamental question of whether two texts were written by the…
When Reranking Hurts: Uncertainty-Based Gating for Few-Shot Reranking
arXiv:2606.31087v3 Announce Type: replace Abstract: Few-shot selection typically assumes that reranking retrieved examples always improves performance. We challenge this view by identifying that the expensive reranking…
Decomposition-Induced Context-Memory Conflict: When Fact-Checking Pipelines Contradict Their Own Source Text
arXiv:2608.10627v1 Announce Type: new Abstract: Decompose-then-verify pipelines, including FActScore-style fact-checkers and long-form factuality evaluators, first split a passage into atomic claims before checking each…
Forensic Reproducibility Audit of a Radiology Vision-Language Model Benchmark: From Intended Protocol to Released Artifact
arXiv:2607.25589v2 Announce Type: replace-cross Abstract: Medical-imaging AI benchmarks combine datasets, DICOM rendering, prompts, provider APIs, automated labels, statistical code, manuscripts, and repository…
Assessing Reliability of BERT-Based Models on Question Answering Tasks
arXiv:2608.10806v1 Announce Type: new Abstract: Reliability estimation of large language models is in many cases as crucial as their accuracy, as reliable models are more trustworthy, robust, and suitable for practical…
The Signal Rail: A Deterministic Motion Grammar for Communicating Conversational Agent State in Terminal Interfaces
arXiv:2608.10689v1 Announce Type: cross Abstract: Terminal interfaces to conversational agents report rich internal state (listening, thinking, executing tools, awaiting input, failing) almost entirely through text,…
CastFSR: A Fast--Slow--Reflect Agentic Reasoning Framework for Context-Aware Time Series Forecasting
arXiv:2608.03031v2 Announce Type: replace Abstract: Time series forecasting is fundamental to decision-making in complex systems, where future dynamics are influenced not only by historical observations but also by…
SynBoost: A Synergistic Framework for Fast Sampling of Diffusion Models
arXiv:2506.13058v2 Announce Type: replace-cross Abstract: Diffusion probabilistic models (DPMs) have demonstrated remarkable success in visual generation. However, their iterative sampling mechanism results in slow…
A Combined Feature-Based Framework for Disguise and Spoofing Detection in Face Recognition Systems
arXiv:2608.08521v2 Announce Type: replace-cross Abstract: Face recognition systems face two distinct, commonly-separated failure modes: spoofing, where an impostor presents a photograph or video of an authorized user,…
TransitReID: Transit OD Data Collection with Occlusion-Resistant Dynamic Passenger Re-Identification
arXiv:2504.11500v3 Announce Type: replace-cross Abstract: Transit Origin-Destination (OD) data are fundamental for optimizing public transit services, yet current collection methods, such as manual surveys,…
UPAIR: Diagnosing Reasoning States via Uncertainty-Progress Alignment for Selective Intervention
arXiv:2607.17188v2 Announce Type: replace Abstract: While test-time scaling improves the problem-solving ability of large reasoning models (LRMs) through additional inference-time computation, it can also exacerbate…
3D Weighted Geometric Graph Neural Networks for Sheep Facial Pain Assessment
arXiv:2608.11050v1 Announce Type: cross Abstract: Deep learning systems perform mainly within the 2D for a single image domain and take the face as a single-dimension representation, losing sight of the 3D anatomy of…
Memory-Augmented Reinforcement Learning Agent for CAD Generation
arXiv:2605.19748v2 Announce Type: replace Abstract: Automatic generation of computer-aided design (CAD) models is a core technology for enabling intelligence in advanced manufacturing. Existing generation methods based…
Blast Radius
arXiv:2608.07440v2 Announce Type: replace Abstract: Agentic coding faces growing problems of affordability and wasted tokens. We introduce Blast Radius, a predictive memory management layer that estimates an incoming…
ForestBench: A Unified Graph Framework for Evaluating Multi-Agent Collaboration
arXiv:2608.08605v2 Announce Type: replace Abstract: Multi-agent systems (MAS) built on Large Language Models (LLMs) are proliferating rapidly, but their heterogeneous execution traces provide no common basis for…
R4DSG: Relative 4D Scene Graph Memory for Object-Centric Question Answering in Long Egocentric Video
arXiv:2608.11017v1 Announce Type: cross Abstract: Long-horizon egocentric video is a rich substrate for wearable AI assistants, but object-centric questions such as where an item was moved, when it last changed state,…
ComBodied Agents: a New Paradigm of Human-Centric Agentic AI
arXiv:2608.10915v1 Announce Type: new Abstract: After an older adult misses a medication dose, a software agent can send another reminder and an embodied agent can bring the medication. Yet neither explains whether the…
RLMOpt: Adaptive Prompt Optimization via Recursive Language Models
arXiv:2608.10471v1 Announce Type: new Abstract: Prompt optimizers automate the search for prompts that improve language-model performance, but existing methods rely on a predefined optimization procedure: the algorithm…
ReCBM: Uncertainty-Gated Relational Reasoning for Concept Bottleneck Models
arXiv:2608.10004v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) provide an interpretable framework by grounding predictions in human-understandable concepts, enabling semantic inspection and test-time…
Flow-Based Generative Modeling for Optimizing Sampling Policies in Compressed Sensing Applications
arXiv:2606.00078v2 Announce Type: replace-cross Abstract: Numerous modern applications in signal processing and medical imaging necessitate acquiring high-dimensional signals under tight resource constraints.…
Situation Graph Prediction for User Perspective Modeling
arXiv:2602.13319v2 Announce Type: replace Abstract: Perspective-aware AI requires modeling evolving internal states---goals, emotions, contexts---not merely preferences. Progress is limited by a data bottleneck: digital…
REDAgentBench: Executable Red Teaming and Faithful Measurement of LLM Agent Systems
arXiv:2608.10669v1 Announce Type: new Abstract: Large language model (LLM) agents combine language-based reasoning with external tools to perform complex tasks. Adversarial inputs can exploit interactions between the…
Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
arXiv:2608.09696v2 Announce Type: replace Abstract: Predicting the answer to interventional ``what if'' questions --- the outcome of an action never taken --- requires a \emph{mechanistic}, causal model, not a curve…
When Agent Automation Becomes Profitable: Quantifying and Insuring Autonomous AI Risk through Trace-Economic Underwriting
arXiv:2606.16465v2 Announce Type: replace Abstract: AI agents can now take irreversible actions in operational systems, but agent-caused losses are still not clearly assigned, priced, or transferred. Providers often…
Compositional Benchmark Synthesis for Hierarchical Human Action Recognition
arXiv:2608.10765v1 Announce Type: new Abstract: Recognizing human behavior across levels of abstraction, from atomic actions to long-horizon intentions, requires data annotated along a semantic hierarchy. Large corpora…
RTSKG: Building a Rail Transit Station Knowledge Graph Dataset
arXiv:2608.11080v1 Announce Type: new Abstract: Rail transit systems play a vital role in urban mobility and economic development. As key components of such systems, rail transit stations function as critical transport…
Rethinking Text-Based Image Retrieval in Specific Domain
arXiv:2608.10524v1 Announce Type: cross Abstract: Driven by the rapid advancement of vision-language representation learning, Text-based Image Retrieval (TBIR) has made notable progress. However, existing benchmarks are…
Temporally Grounded Compositional Camera Motion Understanding via Geometric Knowledge Distillation
arXiv:2608.10932v1 Announce Type: cross Abstract: Understanding camera motion is fundamental to video perception, with applications in spatial intelligence and controllable video generation. Multimodal large language…
Self-Correcting Long-Horizon Search Agents via Tree-Structured Memory
arXiv:2608.10676v1 Announce Type: new Abstract: Large language model (LLM)-based search agents answer questions through multi-step interactions with external environments. However, providing complete execution…
Covert Visual Prompt Injection against Commercial Multimodal Large Language Models
arXiv:2603.29418v2 Announce Type: replace-cross Abstract: Although multimodal large language models (MLLMs) are increasingly deployed in real-world applications, their instruction-following behavior leaves them…
Threat-guided Policy-aware Scene Perturbation for Safe Autonomous Driving with Online Reinforcement Learning
arXiv:2608.10403v1 Announce Type: new Abstract: Reinforcement learning (RL) has shown promising performance in autonomous driving, yet ensuring the safety of online RL policies remains challenging due to insufficient…
TARL: Transaction-Aware Reliable Ledgers for Executable Memory Management in Long-Term Agents
arXiv:2608.03699v2 Announce Type: replace Abstract: Persistent memory helps long-term agents retain knowledge, yet a single update error can repeatedly distort future retrieval and reasoning. Most existing systems…
FITTER: Vocabulary-Agnostic Cross-Domain Inference on Temporal Knowledge Graphs
arXiv:2608.10668v1 Announce Type: new Abstract: Temporal knowledge graphs are central to many uses of the Semantic Web, but existing completion methods assume the entities, relation names, and timestamps to be reasoned…
Unlocking the Power of Medical Tabular Data via Semantic-Aware Multimodal Pre-training
arXiv:2608.10522v1 Announce Type: cross Abstract: While vision-language models dominate medical representation learning, unstructured text lacks the dense, quantitative diagnostic phenotypes inherent in structured…
DiffImaginE: Imagine to Verify Entity Types with Diffusio
arXiv:2608.03025v2 Announce Type: replace Abstract: Multimodal named entity recognition (MNER) determines whether each candidate span and entity-type hypothesis is supported by joint textual and visual evidence.…
Neuroevolution Arena: Nested Ecological Evaluation of Update-and-Inheritance Regimes across Neural Architectures
arXiv:2608.10323v1 Announce Type: new Abstract: Competitive artificial-life systems can rank trained controllers differently under training and ecological evaluation. We present Neuroevolution Arena, a GPU-accelerated…
Decodable But Not Detachable: Training Data Granularity Determines Parametric Modularity in Large Language Models
arXiv:2608.10214v1 Announce Type: new Abstract: Do large language models contain domain-specific parametric shells: concentrated, causally necessary neuron populations whose removal selectively degrades a target domain…
Decision-Aware Approximation of Belief Functions for Evidential Combinatorial Optimization
arXiv:2608.10650v1 Announce Type: new Abstract: Reducing the number of focal elements of a mass function is classically driven by an intrinsic distance, such as Jaccard or Jousselme, that keeps the approximation close…
INSIDE the Student's Mind: Jointly Modeling Latent Reasoning and Action in LLM Student Simulators
arXiv:2608.10492v1 Announce Type: new Abstract: Large Language Model (LLM)-based simulators often reproduce observable actions but fail to capture the underlying reasoning behind them. In education, where student…
TongGuOCR: A Layout-Aware and Token-Augmented OCR MLLM for Chinese Historical Documents
arXiv:2608.07917v2 Announce Type: replace Abstract: Chinese historical documents preserve valuable cultural heritage, but many collections remain accessible only as scanned page images, preventing full-text retrieval,…
JEPA-DNA: Grounding Genomic Foundation Models through Joint-Embedding Predictive Architectures
arXiv:2602.17162v3 Announce Type: replace Abstract: Genomic Foundation Models (GFMs) typically rely on Masked Language Modeling (MLM) or Next-Token Prediction (NTP) to learn the "Laws of Nature". While effective at…
Hierarchical Compositionality for An Assistive AI Agent
arXiv:2608.10330v1 Announce Type: new Abstract: AI agents are increasingly being developed to assist humans in various applications, and Large Language Models and other deep network architectures are considered to be…
SKILLER: Language-Level Reinforcement Learning for Reusable Skill Extraction in Small Language Models
arXiv:2608.10538v1 Announce Type: new Abstract: Agent skills represent a standardized format for packaging procedural knowledge and domain expertise, serving within agent harness systems as an essential mechanism to…
Tree-of-Ideas: Automated Research Ideation via Cross-Trajectory Reasoning over Scholarly Evolution
arXiv:2608.10740v1 Announce Type: new Abstract: Effective research ideation requires moving beyond a static understanding of prior work to trace how research problems and solutions evolve across the literature. Existing…
Improving TensorSketch Using Complex Random Variables
arXiv:2608.10523v1 Announce Type: cross Abstract: \texttt{TensorSketch} by~\cite{pham2013fast,kar2012random} provides efficient sketching algorithms for high-dimensional polynomial kernels $\vec{x}^{\otimes p} \in…
TimeRoute: Time-Aware Modality Routing and Diffusion for Multi-Modal Recommendation
arXiv:2608.10983v1 Announce Type: cross Abstract: Multi-modal recommenders fuse collaborative signals with item modalities such as text, images, and audio, but the usefulness of each drifts over time and at different…
Reinforcement Learning-Based Laser Cutting Machine Parameter Optimization
arXiv:2608.10549v1 Announce Type: new Abstract: Achieving high accuracy in laser-based cutting of optical films requires careful tuning of parameters such as focal length and laser power beam, adjusted according to the…
Selective Prediction Reduces the Negative Effects of Automation Bias Overall but Increases False Negatives
arXiv:2508.07617v2 Announce Type: replace-cross Abstract: AI has the potential to augment human decision making. However, even high-performing models can produce inaccurate predictions when deployed. These inaccuracies,…
How to Dogfood Your AI Chat Agent: A Three-Layer Evaluation Framework with Goal-Directed NPC Simulation
arXiv:2608.09939v1 Announce Type: cross Abstract: Production teams deploying LLM chat agents face a specific quality assurance gap: existing evaluation tools test individual responses or simulate social interactions,…
Hidden in Plain Sight: Diffusion-Based Unrestricted Robotic Attacks on Vision-Language-Action Models
arXiv:2608.10393v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong capabilities in controlling robots across diverse manipulation tasks. However, their adversarial robustness remains…
The CASE Framework: A Multi-Disciplinary Control Architecture for Governing Enterprise Agentic AI
arXiv:2608.10153v1 Announce Type: new Abstract: Enterprises are deploying autonomous AI agents faster than they can govern them, and prevailing approaches stretch a single discipline, typically DevSecOps built for…
Do Personalized Skills Help Coding Agents? An Empirical Study of Developer Interaction Histories
arXiv:2608.10319v1 Announce Type: cross Abstract: Large language model (LLM)-powered agents have rapidly evolved from code-completion tools into solvers of complex software engineering tasks. As developers collaborate…
Quantum Coordination Advantages in AI State-Tracking Tasks: Semantic Compilation and Latent Memory
arXiv:2608.11066v1 Announce Type: cross Abstract: We prove inference-time quantum coordination advantages for specified AI state-tracking tasks. A solver compresses semantic history into a future-accessible boundary…
Policy Convergence and Divergence Across National and Within Regional AI Strategies: A Policy Design Element Analysis
arXiv:2608.11006v1 Announce Type: cross Abstract: Governments worldwide have responded to the rapid expansion of AI by publishing national and regional AI strategies. Comparing national and regional AI strategies to…
MEGA: Self-Evolving Agent Optimization Infrastructure via Wisdom Graph
arXiv:2608.10504v1 Announce Type: new Abstract: As coding agents increasingly handle implementation, the central challenge shifts from building individual agents to building an infrastructure that systematically…
Inferential Capability Does Not Determine Legal Scope
arXiv:2608.10601v1 Announce Type: cross Abstract: Two instruments of EU digital law place inference at their centre and mean different things by it. Article 3(1) of the AI Act uses the capability to infer…
EliSeg: Verified Target Construction for Report-Grounded Abnormality Segmentation
arXiv:2608.07299v2 Announce Type: replace-cross Abstract: Radiology reports describe clinical observations but do not specify executable segmentation targets. They may contain present, negated, prior,uncertain, or…
Field-Localized Forgery Detection for Digital Identity Documents
arXiv:2605.09089v2 Announce Type: replace-cross Abstract: Digital onboarding and eKYC systems used by banks, fintech platforms, telecom providers, and other third-party services commonly verify users by comparing an…
Enhanced Filtering Algorithms for the Euclidean Traveling Salesperson Problem and its variants in Constraint Logic Programming
arXiv:2608.10881v1 Announce Type: new Abstract: The Traveling Salesperson Problem (TSP) is one of the best-known problems in computer science and arises in many engineering applications, such as smart vehicles and…
$\pi$-SUB: A Physics-Informed Synthetic Underwater Benchmark Dataset for Underwater Image Enhancement
arXiv:2608.10589v1 Announce Type: cross Abstract: This paper presents $\pi$-SUB, a physics-informed framework for generating synthetic underwater benchmark datasets that bridges the synthetic-to-real gap for Underwater…
A Methodology for Selecting and Composing Runtime Architecture Patterns for Production LLM Agents
arXiv:2605.20173v2 Announce Type: replace Abstract: Production LLM agents combine stochastic model outputs with deterministic software systems, yet the boundary between the two is rarely treated as a first-class…
Towards Unified Dynamic Face Landmark Detection
arXiv:2608.10346v1 Announce Type: cross Abstract: Although advancements in face landmark detection (FLD) methods continue to push performance boundaries, they overlook two major functional limitations: (1) different…
Agentic Instruction Data Selection: Let DataMaster Interpret Your Intent
arXiv:2608.10579v1 Announce Type: new Abstract: Although existing instruction data selection methods have introduced various metrics, the inherent complexity of real-world datasets makes it impractical for any single…
Predicting Space Groups of Double Perovskites by LLM with Dynamic Few-Shot Learning
arXiv:2608.10483v1 Announce Type: new Abstract: Double perovskites (DPs) offer broad compositional tunability, but predicting the space groups (SGs) of stable structures remains difficult because available datasets are…
Closed-Loop LLM Co-Pilots for Digital Agriculture
arXiv:2608.09949v1 Announce Type: new Abstract: This study evaluates the application of Large Language Models (LLMs) in complex biological systems, evolving from data analysis to autonomous, AI-guided experimentation.…
Conversational versus Dashboard Explainable AI for UAV Intrusion Detection: An Empirical Study of Operator Trust and Reliance
arXiv:2608.10434v1 Announce Type: new Abstract: Machine learning-based Intrusion Detection Systems (IDS) have demonstrated superior performance in securing Unmanned Aerial Vehicle (UAV) networks. However, the…
Conversational Orchestration for Organic 6G
arXiv:2608.10714v1 Announce Type: cross Abstract: The Organic 6G vision of a network of networks spanning an edge-cloud continuum complemented by non-terrestrial resources requires, to realize its promise, service…
DIMOS: Disentangling Instance-level Moving Object Segmentation
arXiv:2606.12826v2 Announce Type: replace-cross Abstract: Moving instance segmentation (MIS) attracts increasing attention due to its broad applications in traffic surveillance, autonomous driving, and animal tracking.…
Generating Attacks for LLMs with GFlowNets
arXiv:2608.10171v1 Announce Type: new Abstract: The rapid advancement of Large Language Models (LLMs) has facilitated their ubiquitous integration into various domains, leading to widespread adoption. However, this…
IO Factory: Simulating AI-Enabled Influence Campaigns at Scale
arXiv:2608.10920v1 Announce Type: new Abstract: We introduce IO Factory, an AI-driven framework for simulating information and influence campaigns as fully integrated, traceable processes. The threat of digital…
KAYROS: An Anytime and Exact Open-Source Solver for Duration-Minimization Time-Dependent Vehicle Routing. A Technical Report and a Case Study in Human-AI Engineering
arXiv:2607.23116v2 Announce Type: replace-cross Abstract: Time-dependent routing recognizes that the same journey can take a different time depending on when it begins. Under duration minimization, even the departure…
When Does Critique Improve AI-Assisted Theoretical Physics? SCALAR: Structured Critic--Actor Loop for Agentic Reasoning
arXiv:2605.06772v2 Announce Type: replace Abstract: As large language models (LLMs) show increasing promise on research-level physics reasoning tasks and agentic AI becomes more common, a practical question emerges: How…
Rationale-Guided Learning for Multimodal Emotion Recognition
arXiv:2608.10448v1 Announce Type: new Abstract: Multimodal emotion recognition in conversation (MERC) requires understanding complex interactions between verbal and non-verbal cues. However, most existing approaches…
A Single Atom in Front of a Mirror is a Universal Reservoir Computer
arXiv:2608.10382v1 Announce Type: cross Abstract: Universal approximation in reservoir computing is typically associated with a class of reservoirs. We show that universality can be associated with a single reservoir,…
Entropy-Centric Explainable AI for Remote Sensing Image Segmentation
arXiv:2608.11064v1 Announce Type: cross Abstract: Artificial intelligence (AI) has become a powerful approach to solving complex problems in critical domains. Many concerns arise regarding the decision-making process of…
Persistent Recursive Worlds Enable Autonomous Software Evolution
arXiv:2608.10450v1 Announce Type: cross Abstract: Complex software systems develop over timescales that exceed the lifespan of any individual coding agent. Most agentic software systems preserve continuity through…
sLTN: Structural Logic Tensor Networks
arXiv:2608.11136v1 Announce Type: new Abstract: Logic Tensor Networks (LTN) provide a neurosymbolic framework in which first-order logic is interpreted through tensor operations, enabling logical constraints to be…
From Talking to Singing: A New Challenge for Audio-Visual Deepfake Detection
arXiv:2605.27944v2 Announce Type: replace Abstract: With rapid advances in audio-visual generative models, reliable forgery detection becomes increasingly critical. Existing methods for audio-visual deepfake detection…
Leveraging Large Language Models for Causal Discovery: a Constraint-based, Argumentation-driven Approach
arXiv:2602.16481v2 Announce Type: replace Abstract: Causal discovery seeks to uncover causal relations from data, typically represented as causal graphs, and is essential for predicting the effects of interventions.…
X2C: A Large-Scale Benchmark for Nuanced Humanoid Facial Expression Imitation
arXiv:2505.11146v4 Announce Type: replace-cross Abstract: Fine-grained facial expression transfer from humans to humanoid agents presents a unique pattern recognition challenge due to the significant domain gap between…
Workflow Cards: Structured Summaries of Workflow Executions Using Provenance Data
arXiv:2608.11022v1 Announce Type: cross Abstract: Model Cards and Data Cards have demonstrated the value of structured, human-readable documentation for machine learning artifacts, capturing their context, parameters,…
Toward a Theory of Value in AI Alignment
arXiv:2608.10327v1 Announce Type: new Abstract: Can AI systems be aligned to human values? The popularization of large language models (LLMs) and multi-modal foundation models has seen a rise in harms spanning from…
Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education
arXiv:2605.15850v3 Announce Type: replace-cross Abstract: In recent years, generative AI (GenAI) in educational settings has become ubiquitous in university students' daily lives, despite its potential to induce…
EventCoT: Event-centric Video Chain-of-thought for Reasoning Temporal Localization
arXiv:2607.04872v2 Announce Type: replace-cross Abstract: Reasoning temporal localization (RTL) requires a model to generate an answer that itself contains the time interval supporting it, coupling high-level reasoning…
Hybrid Token Compression for Vision-Language Models
arXiv:2512.08240v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) rely on hundreds of visual tokens, leading to high computational and memory costs. Existing compression methods face a trade-off:…
Surgical WAM: A World-Action Model for Data-Efficient Surgical Robot Learning
arXiv:2608.11204v1 Announce Type: cross Abstract: Learning reliable surgical manipulation policies is bottlenecked by the scarcity of action-labeled demonstrations: teleoperated surgical robot (e.g., dVRK) trajectories…
Expert-Guided g-computation with Large Language Models for Estimating Causal Effects on Timings: Applications to Hospital Quality Improvement
arXiv:2608.10339v1 Announce Type: cross Abstract: Hospital quality improvement (QI) programs routinely face multiple candidate interventions to optimize hospital flow, but existing methods struggle to estimate and rank…
Dynamic Context Adapters: Efficiently Infusing History into Vision-and-Language Models
arXiv:2608.10525v1 Announce Type: cross Abstract: Historical context integration presents a fundamental challenge for Vision-Language Models (VLMs) in sequential decision-making tasks. Current VLMs process visual inputs…
Planning Task Shielding: Detecting and Repairing Flaws in Planning Tasks through Turning them Unsolvable
arXiv:2604.07042v3 Announce Type: replace Abstract: Most research in planning focuses on generating a plan to achieve a desired set of goals. However, a goal specification can also be used to encode a property that…
A HamNoSys-Guided Dataset and Baselines for Fine-Grained Isolated Handshape Recognition in Sign Language
arXiv:2608.10588v1 Announce Type: cross Abstract: Purpose: Fine-grained handshape recognition supports computational sign-language transcription, recognition, and translation, but broad, phonetically defined visual…
Music Interpretation and Emotion Perception: A Computational and Neurophysiological Investigation
arXiv:2506.01982v5 Announce Type: replace-cross Abstract: This study investigates emotional expression and perception in music performance using computational and neurophysiological methods. The influence of different…
Automating and Scaling Behavioral Scientific Research on AI Agents
arXiv:2608.10030v1 Announce Type: new Abstract: As AI agents are increasingly deployed in complex environments, understanding their behaviors becomes critical. Yet behavioral scientific research on AI agents remains…
HexEval: An Evidence-Driven Hexagonal Framework for Multidimensional Scholar Assessment
arXiv:2608.10584v1 Announce Type: new Abstract: Scholar assessment plays a fundamental role in faculty recruitment, funding allocation, academic promotion, and talent discovery. Existing scholar assessment methods…
Mitigating Bus Bunching with Reinforcement Learning Enhanced by Semantic Stop Embedding
arXiv:2608.10207v1 Announce Type: new Abstract: Bus bunching degrades service regularity and increases passenger waiting in high-frequency transit. Existing reinforcement-learning-based holding controllers primarily…
Optimal Stopping of Self-Refining Foundation Models
arXiv:2608.10729v1 Announce Type: cross Abstract: Foundation models can improve their outputs through a self-refinement process driven by external feedback. In this process, the model is embedded in an iterative loop…
SafeCap: Improving LVLM Safety with Image Captioning Reinforcement Learning
arXiv:2608.10513v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) remain vulnerable to jailbreak attacks that exploit visual inputs to bypass safety alignment inherited from their language…
From Faulty Memories to Corrected Actions: Dependency-Guided Rollback Repair for Memory-Augmented Agents
arXiv:2608.10502v1 Announce Type: new Abstract: Persistent memory lets language-model agents reuse information across sessions, but it also makes errors durable: a poisoned, stale, or misattributed record can alter…
GeoForge: Non-Parametric Self-Evolving Agents for Earth-Observation Reasoning
arXiv:2608.10494v1 Announce Type: new Abstract: Earth observation (EO) agents construct scientifically valid tool workflows and ground their conclusions in current geospatial evidence. This is challenging because EO…
Curate Before You Connect: Identity and Ontology Tagging in a Production Knowledge Graph
arXiv:2608.10644v1 Announce Type: new Abstract: Extraction produces candidate entities and relationships; writing them into a graph is where identity is decided, and identity decisions are destructive in a way…
StructReward: Efficient Structured Process Rewards for Self-Correcting Multimodal Reasoning
arXiv:2608.08326v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as an effective approach for improving multimodal reasoning. However, most existing methods evaluate…
HoosierHelp: Benchmarking LLM Agents for Social Service Navigation
arXiv:2608.09946v1 Announce Type: cross Abstract: Social service navigation requires connecting help-seeking individuals to resources that satisfy their needs and specific constraints. Although LLM agents offer a…
TrAC: Trace-Conditioned Answer Consistency for Efficient Uncertainty Quantification in LLMs
arXiv:2608.00422v2 Announce Type: replace Abstract: Large language models (LLMs) can generate fluent reasoning traces that nevertheless lead to incorrect answers, making response-level uncertainty estimation important…
MVTrack: Ultrafast Appearance-Free Moving Object Tracking from Compressed Bitstreams
arXiv:2608.10790v1 Announce Type: cross Abstract: Deploying modern video trackers at scale is bottlenecked by the computational cost of RGB-based object detectors. To this end, we present MVTrack, an ultrafast tracker…
Protecting Creative Writing Copyright against AI Imitation via Implicit Watermarking
arXiv:2504.00035v4 Announce Type: replace-cross Abstract: Large language models (LLMs) enable powerful knowledge injection through approaches such as in-context learning and fine-tuning, but they also introduce new…
XCoT-VLA: Executable Chain-of-Thought for Vision-Language-Action Driving
arXiv:2608.10976v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models can connect scene understanding, semantic reasoning, and trajectory generation for autonomous driving. However, verbose…
Rescene: band-limited stochastic forcing turns a frozen neural weather operator into a climate emulator
arXiv:2608.09971v1 Announce Type: cross Abstract: Over the past few years, the rapid development of machine learning (ML) models for weather forecasting has produced deterministic models whose medium-range skill matches…
Frozen Brain-MRI Foundation Models Are Site Fingerprints
arXiv:2608.10295v1 Announce Type: cross Abstract: Frozen foundation-model (FM) embeddings are increasingly used as off-the-shelf brain-MRI representations, on the assumption that they capture anatomy. We audit what they…
Ouroboros: A Self-Developing Frontier Coding Agent with Reviewed Core Evolution
arXiv:2608.08311v2 Announce Type: replace-cross Abstract: We present Ouroboros, a self-developing agent harness whose tools, prompts, context assembly, and core implementation improve through reviewed commits that…
ImpactHO: Importance-Aware KV Cache Transfer for Multi-User Edge LLM Handover
arXiv:2608.10545v1 Announce Type: cross Abstract: Edge LLMs must preserve inference continuity when a user hands over between edge nodes, requiring key-value (KV) cache transfer to the target node. However, simultaneous…
MasDrift: Benchmarking Authorization Preservation Across Multi-Agent Architectures
arXiv:2608.07556v2 Announce Type: replace-cross Abstract: Multi-agent systems (MAS) decompose long-horizon tasks across supervisors and subagents, but delegated goals do not necessarily carry their original…
AttriMem: Attribution-Guided Process Feedback for Agent Memory Construction
arXiv:2607.21106v3 Announce Type: replace Abstract: Effective memory is crucial for LLM agents, yet constructing it effectively remains challenging. A memory-construction policy decides what information to extract,…
LaViT: Aligning Latent Visual Thoughts for Multi-modal Reasoning
arXiv:2601.10129v2 Announce Type: replace-cross Abstract: Current multimodal latent reasoning often relies on external supervision (e.g., auxiliary images), ignoring intrinsic visual attention dynamics. In this work, we…
Graphical Models of False Information and Fact Checking Ecosystems
arXiv:2208.11582v2 Announce Type: replace-cross Abstract: The wide spread of false information online, including misinformation and disinformation, has become a major problem for our highly digitised and globalised…
ThinkRetrieve: Retrieval-Augmented Reasoning Traces for Test-Time Scaling
arXiv:2608.10928v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) improve performance by allocating additional inference-time compute to generate extended chain-of-thought reasoning. However, recent studies…
Pricing Access to Dynamic Information Services
arXiv:2510.09859v5 Announce Type: replace-cross Abstract: A provider sells a \emph{dynamic information service}---a real-time, capacity-constrained process that resolves a customer's uncertainty---to customers who…
Beyond Decision Boundaries: Relational Geometry Attacks on Contrastive Embedding Manifolds
arXiv:2608.10237v1 Announce Type: new Abstract: Contrastive learning and Siamese embedding models have become the foundation of modern verification systems, where decisions are governed not by discrete classification…
DegradeQuery: Counterfactual Tuple Pretraining for Context-Aware PROTAC Degradation Prediction
arXiv:2608.10595v1 Announce Type: cross Abstract: Proteolysis-targeting chimeras (PROTACs) induce protein degradation by recruiting a target protein to an E3 ubiquitin ligase, making degradation a joint outcome of the…
Smart Enough to Go Extinct? An Evolutionary Challenge to the Value of General Intelligence and Its Ethical Implications for AGI
arXiv:2608.10730v1 Announce Type: cross Abstract: The pursuit of artificial general intelligence (AGI) rests on a seemingly self-evident premise: that general intelligence, the kind of flexible, domain-general cognitive…
Interpreting Language Model Hidden States at Scale
arXiv:2608.10260v1 Announce Type: new Abstract: Lens methods interpret large language models (LLMs) by mapping intermediate activations to the output vocabulary, revealing how next-token predictions develop through the…
Self-evolving Agentic Customer Support System at LinkedIn
arXiv:2608.10224v1 Announce Type: new Abstract: Enterprise support agents operate in rapidly changing environments where policies, product capabilities, and knowledge bases evolve continuously, making static assistants…
EvoMem: Memory-Augmented Evolution for Code Optimization
arXiv:2608.10795v1 Announce Type: new Abstract: Successful mutation strategies in evolutionary code search may contain reusable knowledge that is useful beyond a single run, and in some cases may transfer across related…
Evidence-Grounded Trustworthy Multimodal Reasoning and Evaluation Benchmark in Complex Urban Scenes
arXiv:2608.10954v1 Announce Type: cross Abstract: While Multimodal Large Language Models (MLLMs) demonstrate impressive performance in benign scenarios, their cognitive reliability deteriorates significantly in complex…
Causality Sum Rules in Conventional Scattering Matrices
arXiv:2608.10427v1 Announce Type: cross Abstract: Scattering matrices are the standard experimental and computational description of photonic and electromagnetic devices. Passivity is explicit in the conventional…
FedCGR: Federated Cross-Domain Generative Recommendation
arXiv:2608.10929v1 Announce Type: new Abstract: Cross-domain recommendation (CDR) transfers preference knowledge across related domains, but federated deployment makes cross-domain alignment difficult because the…
The GenAI Catch-22: Use of Generative Artificial Intelligence in Norwegian Newsrooms During the 2025 Parliamentary Election
arXiv:2608.10773v1 Announce Type: cross Abstract: The increasing use of Generative Artificial Intelligence (GenAI) in journalism raises concerns about possible detrimental effects both on journalism and its democratic…
Continuous Interaction Diffusion: A Diffusion-Native Runtime for Asynchronous Tool-Augmented Reasoning
arXiv:2608.10438v1 Announce Type: new Abstract: Large language models increasingly rely on external tools to access up-to-date information, perform computation, and interact with the outside world. For autoregressive…
Thought-Level Beam Search for Reasoning
arXiv:2608.08020v2 Announce Type: replace Abstract: Test-time compute scaling is a primary driver of performance in large reasoning models (LRMs), but extreme inefficiency bounds current approaches, shifting the…
The Deliberative Deficit: An Empirical Critique of LLMs in Democratic Discourse
arXiv:2608.10186v1 Announce Type: cross Abstract: LLMs are increasingly deployed in settings that require collective reasoning on complex, value-laden problems. Confidence in these deployments rests largely on…
Evaluation and Hardening of LLM System Instructions Against Extraction via Encoding Attacks
arXiv:2604.01039v3 Announce Type: replace-cross Abstract: System Instructions in Large Language Models (LLMs) are commonly used to enforce safety policies, define agent behavior, and protect sensitive operational…
Small Foundation Models of Human Cognition and Behaviour
arXiv:2608.05224v3 Announce Type: replace Abstract: Large language models fine-tuned on human behavioural data have emerged as general-purpose cognitive proxies, but the scale this requires, and whether these models…
Astrolabe: Balancing Load in LLM Serving with Randomized Prediction-Guided Scheduling
arXiv:2508.03611v3 Announce Type: replace-cross Abstract: This paper presents Astrolabe, a randomized prediction-guided scheduler for one-shot request dispatch in multi-instance large language model (LLM) serving.…
Nutrition Data Infrastructure for the AI Era: Operationalizing FAIR for Agent-Mediated Research
arXiv:2608.10363v1 Announce Type: new Abstract: AI agents can accelerate nutrition research, but their analyses inherit the identity, semantic, and release ambiguities of the underlying data. We present Nutrition Data…
Patients With Personality: Realistic Patient Simulation through Controlled Diversity and Selective Disclosure
arXiv:2606.17441v2 Announce Type: replace-cross Abstract: Simulating realistic patient interactions is a key requirement to testing clinical applications of LLMs at scale without time-consuming and expensive user…
Never Stop Speaking: a Denial-of-Service Attack on End-to-End Speech Language Models
arXiv:2608.10405v1 Announce Type: cross Abstract: Many studies have shown that specially crafted inputs can induce large language models (LLMs) to generate excessively long outputs, resulting in significant…
Whisper-Aware LLM: Self-Supervised Uncertainty Learning for Robust Whispered Speech Recognition
arXiv:2608.10836v1 Announce Type: cross Abstract: The signal ambiguity of whispered speech drives ASR systems toward two opposing failure modes: failing to capture whispered speech or hallucinatory transcription of…
ReMMD: Realistic Multilingual Multi-Image Agentic Verification for Multimodal Misinformation Detection
arXiv:2606.24112v2 Announce Type: replace Abstract: Multimodal misinformation detection is increasingly important because viral posts now combine long multilingual narratives, several images, mixed provenance, and…
VERDICT: Training-Free Step-Wise Verification of Multimodal Reasoning via Disagreement-Aware Consensus
arXiv:2608.10665v1 Announce Type: new Abstract: Multimodal large language models often generate reasoning chains containing subtle errors that lead to incorrect answers. Current verification approaches have notable…
SkillZip: Evaluation-Free Skill Compression for Self-Evolving Agents by Discovering Reusable Structure
arXiv:2608.11079v1 Announce Type: new Abstract: Self-evolving agents accumulate reusable skills by appending successful procedures and failure fixes. Over time, the same requirement is often restated in several…
SkillLens: Visual Skill Cards for Retrieval-Augmented GUI Action Prediction and On-Policy Distillation
arXiv:2608.10775v1 Announce Type: new Abstract: Computer-using agents can perceive rich software interfaces, yet their decisions often lack visual procedural memory: they may recognize individual controls without…
CuSearch: Curriculum Rollout Sampling via Search Depth for Agentic RAG
arXiv:2605.11611v3 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a promising paradigm for training agentic retrieval-augmented generation (RAG) systems from…
The Gaussian-Multinoulli Restricted Boltzmann Machine: A Potts Model Extension of the GRBM
arXiv:2505.11635v2 Announce Type: cross Abstract: Many real-world tasks, from associative memory to symbolic reasoning, benefit from discrete, structured representations that standard continuous latent models can…
On Understanding, Identifying, and Mitigating Vulnerabilities in Agentic Large Language Models
arXiv:2608.10530v1 Announce Type: cross Abstract: Large Language Models (LLMs) have undergone a shift from stateless conversational interfaces to autonomous agents capable of multi-step planning, tool invocation, code…
Learning and Structurally Validating Simulation Scenario Continuations in Dynamic Graph Systems
arXiv:2607.21421v2 Announce Type: replace Abstract: Data-driven generative models can extend partially observed simulation trajectories into ensembles of alternative future scenarios. However, consistency with a learned…
MESA:Task-Adaptive Multi-Structure Evidence Selection for Long-Horizon Agent Memory
arXiv:2608.10108v1 Announce Type: new Abstract: Long-horizon agents accumulate trajectories spanning hundreds of interleaved reasoning, action, and observation steps, where answering a query may depend on evidence…
The Epistemic Politics of AI Anthropomorphism
arXiv:2608.00961v2 Announce Type: replace-cross Abstract: AI anthropomorphism is typically treated as a problem of user misperception requiring institutional correction. Users who engage in sustained or relational…
Beyond Forecasting: Recasting Volatility Control as a Routing Problem
arXiv:2608.10375v1 Announce Type: cross Abstract: Volatility control converts risk estimates into portfolio exposure, yet existing approaches often rely on a fixed volatility estimator or a pre-defined control rule that…
Navigation Alone Is Not Enough: Evaluating Explanatory Assistive UI Agents
arXiv:2608.09944v1 Announce Type: cross Abstract: Modern web interfaces are increasingly difficult to use with screen readers, particularly when pages update dynamically or hide important structure behind visual layout.…
Anomaly Detection and Root Cause Analysis for Microservice Systems
arXiv:2606.09942v3 Announce Type: replace-cross Abstract: Microservice systems are widely used to build cloud applications, yet their complexity makes failures inevitable, degrading user experience and causing economic…
Unsupervised Detection of Groundwater Storage Anomalies in Ghana Using GRACE Satellite Data
arXiv:2608.10233v1 Announce Type: cross Abstract: Groundwater variability in Ghana remains poorly characterized due to limited long-term in-situ observations. This study investigates groundwater storage anomalies using…
A Gateway Architecture for Enterprise MCP Authentication: Unifying Heterogeneous Auth, Identity Delegation, and the User / Non-User Persona Problem
arXiv:2608.10760v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) has become the de-facto interface for connecting LLM agents to enterprise tools, and adoption has been explosive: within a year, large…
SDDBMs: Soft Denoising Diffusion Bridge Models
arXiv:2608.08594v2 Announce Type: replace Abstract: Diffusion bridge models leverage Doob's \(h\)-transform to construct stochastic transports between arbitrary endpoint distributions, and have shown strong potential in…
Entropy-based Code Adversarial Translation for Real-world Repository Migration
arXiv:2608.09273v2 Announce Type: replace Abstract: LLMs have demonstrated strong capabilities in code generation and automated program repair, but migrating an entire repository rarely produces a runnable application…
MaskFlow: Precise, Consistent and Seamless Regional Image Editing
arXiv:2608.06929v2 Announce Type: replace-cross Abstract: Regional image editing has attracted considerable attention for its spatial controllability. Although instruction-based and mask-reference-based editing methods…
EviBack: Search-Agent Reinforcement Learning via Evidence-Constrained Teacher Backoff
arXiv:2607.23955v3 Announce Type: replace Abstract: Reinforcement learning enables Agentic RAG systems to learn multi-turn search from verifiable outcome rewards, but all- zero rollout groups provide no comparative…
Hypothesis Frontier: Verifier Guided LLM and Symbolic Search for First-Order Induction
arXiv:2608.10843v1 Announce Type: new Abstract: First-order concept synthesis asks a system to infer one formula that classifies labeled objects consistently across several finite relational structures. Every candidate…
Long-Horizon AI Research for Grothendieck Constant: A Case Study in Human-AI Mathematical Collaboration
arXiv:2608.11195v1 Announce Type: new Abstract: AI agents are increasingly used in mathematics research, but it is often unclear how to use them effectively. Towards this, we present an extensive case study of how AI…
Exploring Semantic Stability Across Reviews in the Linux Kernel
arXiv:2608.10101v1 Announce Type: cross Abstract: Code review is credited with substantially changing a patch's code between its first submission and the version that eventually lands. However, prior work typically…
Closing a 17-Year Gap: Algorithmic Detection and Empirical Prevalence of Rank Reversal in Multi-Criteria Decision Analysis
arXiv:2508.00129v2 Announce Type: replace Abstract: Rank Reversal, where the relative order of alternatives changes in ways that violate axioms of rational decision-making, is a well-documented threat to the reliability…
Eleven Years of BRACIS: A Meta-Scientific Study of the Brazilian Conference on Intelligent Systems
arXiv:2608.09964v1 Announce Type: cross Abstract: The Brazilian Conference on Intelligent Systems (BRACIS) is the main national venue for Artificial Intelligence research in Brazil, hosted by the Brazilian Computer…
What We Know about Responsible AI Practices in Industry: A Half Decade of Empirical Research
arXiv:2608.10431v1 Announce Type: cross Abstract: Responsible AI (RAI) has become a central concern for technology companies, regulators, and the public. How industry practitioners interpret, implement, and sustain RAI…
$\mathrm{ECI}_{\mathrm{sem}}$: Semantic Residual Effective Contrastive Information for Evaluating Hard Negatives
arXiv:2603.20990v4 Announce Type: replace-cross Abstract: Hard-negative source selection for dense retrieval is usually decided only after fine-tuning and downstream evaluation. We propose ECIsem, a validity-weighted…
CoEvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification
arXiv:2604.01687v3 Announce Type: replace Abstract: Anthropic proposes the concept of skills for LLM agents to tackle multi-step professional tasks that simple tool invocations cannot address. A tool is a single,…
A Comparative Evaluation of Deep Learning Object Detection Models on a Real-World Multi-Plant Dataset from Africa
arXiv:2608.11053v1 Announce Type: cross Abstract: The application of computer vision in agriculture has shown significant potential for improving crop monitoring and precision farming. However, many existing approaches…
TRACE: Trustworthy Retrieval-Augmented Conversational Engine
arXiv:2608.10176v1 Announce Type: new Abstract: Public service chatbots are expected to deliver recommendations from an underlying public service directory, while also making sure that the recommendations respect…
Comprendia: AI-Augmented Code Comprehension
arXiv:2608.10290v1 Announce Type: cross Abstract: Comprendia is an Eclipse plugin that integrates structural dependency visualization with LLM-powered code explanation on a shared interactive graph for Java program…
MedUP: Awakening Unified Understanding and Perception in Medical Vision-Language Models
arXiv:2608.10635v1 Announce Type: cross Abstract: Medical Vision-Language Models (Med-VLMs) excel at verbalizing visual content, yet precise visual perception, segmentation, and grounding remain challenging. Existing…
CARD: Controlled Agentic Reddit Discussions for Credit Card Simulation
arXiv:2608.09790v2 Announce Type: replace Abstract: Online credit card discussions provide a natural setting for studying how consumers communicate about financial products. Simulating these discussions requires more…
GraFine: Retrieval-Time Refinement for Efficient Graph RAG over Corpus Graphs
arXiv:2601.18579v2 Announce Type: replace-cross Abstract: Graph RAG on corpus graphs enhances retrieval by leveraging intermediate node content as contextual clues to uncover unretrieved oracle nodes. However, existing…
Beyond Detection: Evaluating Defensive LLMs Against AI-Generated Social Engineering in Live Turn-by-Turn Interaction
arXiv:2608.10239v1 Announce Type: new Abstract: Generative AI makes social-engineering attacks more fluent, adaptive, and scalable, increasing the need for LLM-based de- fenders that can protect users during ongoing…
Cross-View Sequential Visual Localization with Spatio-Temporal Context Modeling for Autonomous Driving
arXiv:2608.10660v1 Announce Type: cross Abstract: Continuous and reliable localization is essential for autonomous driving. Cross-view visual localization matches ground images with satellite maps, providing…
MAP-Graph: Provenance-Aware Shared Memory for Multi-Agent Workflows
arXiv:2608.10509v1 Announce Type: new Abstract: Shared memory helps language-model agents reuse information across long workflows, yet relevant evidence may not be admissible for a particular agent or action. Because…
Evidence-Based Scientific Question Discovery: A Framework with Historical Backtesting
arXiv:2608.09968v1 Announce Type: cross Abstract: Current AI systems are optimized for answering questions; the scientific enterprise is bottlenecked earlier, at discovering the questions worth investigating. We present…
Post-Hoc Sparse Coding of Latent Communication Between Vision-Language Model Agents
arXiv:2608.10198v1 Announce Type: new Abstract: Latent-space communication allows heterogeneous vision-language model agents to exchange continuous representations without serializing visual and reasoning states into…
MarkNull: Model-Agnostic Watermark Removal in AI-Generated Images via On-Manifold Latent Manipulation
arXiv:2608.10166v1 Announce Type: cross Abstract: Digital watermarking has emerged as a critical technique for provenance and copyright attribution in AI-generated imagery, yet its robustness against realistic,…
A Fixed-Point Neural Operator for Size- and Functional-Transferable Hamiltonian Prediction
arXiv:2606.14498v2 Announce Type: replace-cross Abstract: Predicting the Kohn-Sham Hamiltonian with machine learning can accelerate density functional theory while retaining access to molecular orbitals, energy levels,…
MultiView-Bench: A Diagnostic Benchmark for World-Centric Multi-View Integration in VLMs
arXiv:2607.08970v3 Announce Type: replace-cross Abstract: Recent benchmarks for VLMs largely assess single- or limited-view perception, leaving untested the core cognitive ability to integrate observations across…
Pretrained Optimization Model for Zero-Shot Black Box Optimization
arXiv:2405.03728v3 Announce Type: replace-cross Abstract: Zero-shot optimization involves optimizing a target task that was not seen during training, aiming to provide the optimal solution without or with minimal…
Ablation-Corrected Evaluation of Attribution Maps in Echocardiographic Ejection-Fraction Models
arXiv:2607.13738v5 Announce Type: replace-cross Abstract: Attribution maps for echocardiographic ejection-fraction models are evaluated by their overlap with an expert left-ventricular annotation, compared against a…
CARE: Confidence-Aware Reasoning for Reliable Medical VQA
arXiv:2608.10964v1 Announce Type: cross Abstract: Reinforcement Fine-Tuning (RFT) has enabled medical Multimodal Large Language Models (MLLMs) to produce Chain-of-Thought (CoT) reasoning for visual question answering,…
OpenDPDv2: A Unified Learning and Optimization Framework for Neural Network Digital Predistortion
arXiv:2507.06849v3 Announce Type: replace-cross Abstract: Neural network (NN)-based Digital Predistortion (DPD) improves linearization for wideband radio frequency (RF) power amplifiers (PAs) but often increases the…
Token-Based Detection of Spurious Correlations in Vision Transformers
arXiv:2509.04009v2 Announce Type: replace-cross Abstract: Due to their powerful feature association capabilities, neural network-based computer vision models have the ability to detect and exploit unintended patterns…
MazzikaAI: A knowledge-based performance-to-prompt compiler for real-time Arabic maqam accompaniment with a streaming text-to-music model
arXiv:2608.10360v1 Announce Type: cross Abstract: Arabic maqam music microtonal, modal, and built on ornamented call and response is among the traditions most underserved by generative music models, whose training…
SpeedTuning: Speeding Up Policy Execution with Lightweight Reinforcement Learning
arXiv:2608.09138v2 Announce Type: replace-cross Abstract: While learned robotic policies hold promise for advancing generalizable manipulation, their practical deployment is often hindered by suboptimal execution…
FUSE: Frame-Unified Stress Estimation from Facial Video
arXiv:2608.10442v1 Announce Type: cross Abstract: Automatic stress detection from facial video offers a practical path to non-intrusive affect monitoring, yet existing video-based approaches commonly decompose full…
GAM-Agent: Game-Theoretic and Uncertainty-Aware Collaboration for Complex Visual Reasoning
arXiv:2505.23399v2 Announce Type: replace Abstract: We propose GAM-Agent, a game-theoretic multi-agent framework for enhancing vision-language reasoning. Unlike prior single-agent or monolithic models, GAM-Agent…
Hand-Written PTX Tensor-Core GEMM Kernels: A Multi-Precision Study on NVIDIA L4
arXiv:2608.10103v1 Announce Type: cross Abstract: High-performance Tensor Core kernels rely on a low-level PTX pipeline built from asynchronous data movement with cp.async, warp-level matrix loads with ldmatrix, and…
Operationalising Relative Causal Knowledge: Backbone Identifiability from Private Reports on a Shared Outcome
arXiv:2608.10664v1 Announce Type: new Abstract: The Relativity of Causal Knowledge (RCK) explains how a network of agents with different structural causal models can exchange causal knowledge through a shared…
Reasoning Shortcuts and Value Symmetries: What Symmetry Permits, Architecture Realizes, and Optimization Selects
arXiv:2608.10420v1 Announce Type: new Abstract: Reasoning shortcuts are solutions of a neurosymbolic system's rules that produce correct predictions through unintended concepts. A recent framework of Takemura, Inoue,…
Modelling Geographic Atrophy Progression using Implicit Neural Representations
arXiv:2608.10807v1 Announce Type: cross Abstract: Age-related Macular Degeneration (AMD) is the major cause of blindness in the Western world. Its late dry phase is characterised by irreversible atrophic areas, namely…
Contextual Information Policy Optimization for Search Agents
arXiv:2608.06128v3 Announce Type: replace Abstract: Search agents extend large language models beyond static parametric memory by enabling them to acquire and use external evidence during multi-step reasoning. For…
DashArena: Benchmarking LLMs on Interactive Analytic Dashboard Generation
arXiv:2608.10567v1 Announce Type: new Abstract: Analytic dashboards combine coordinated views and interactions for data exploration and decision-making. Recent models can generate them from data and natural-language…
Reconfiguration of pivoting cube ensembles under local sensing constraints using geometric deep learning
arXiv:2509.03140v2 Announce Type: replace-cross Abstract: We demonstrate that local sensing is sufficient for effective global reconfiguration of homogeneous pivoting cube modular robots in two dimensions. While cube…
PinpointQA: A Benchmark for Small Object-Centric Spatial Understanding in Indoor Videos
arXiv:2604.08991v3 Announce Type: replace-cross Abstract: Reliable embodied interaction in indoor environments requires agents to precisely localize small everyday objects from visual observations. Yet this fundamental…
Persona Conditioning as an Assessor-Sensitivity Probe for LLM-Based IR Evaluation
arXiv:2608.10385v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as relevance assessors in information retrieval (IR) evaluation, raising questions about how assessor framing affects…
Putting Registers to Work: Task Registers for Token Pruning in Vision Transformers
arXiv:2608.10989v1 Announce Type: cross Abstract: Token-pruning policies are usually designed for a single recognition pipeline, but pretrained Vision Transformers are reused across tasks with different spatial demands.…
SBCO: Self-Supervised, Verifier-Grounded Harness Optimization For Planning Agents
arXiv:2608.10157v1 Announce Type: new Abstract: Self-improving agents seek to reduce the human engineering effort behind AI systems by enabling them to evolve and self-improve their performance over time. Recently,…
MIRA: Medical Image Reflection for Agentic Diagnosis
arXiv:2608.10827v1 Announce Type: cross Abstract: Medical visual agents can use tools to inspect images and retrieve external knowledge, but indiscriminate tool use may introduce noisy or misleading evidence. Reliable…
Fast and Memory-Efficient Wavelet Convolutions via I/O-Aware Reformulation
arXiv:2608.10805v1 Announce Type: cross Abstract: Wavelet convolution (WTConv) has emerged as an increasingly popular drop-in replacement for standard convolutions, expanding a network's receptive field exponentially…
GitSkills: A Dataset of Agent Skills on GitHub
arXiv:2608.10906v1 Announce Type: cross Abstract: An agent skill is a folder containing a SKILL.md file with instructions for a language-model agent, optionally accompanied by scripts and reference files. The agent…
"YES! YES! I absolutely love this insight!" Affirmative Narration as Interactional Strategy in Dialogues with LLM Chatbots
arXiv:2607.28646v2 Announce Type: cross Abstract: This article analyses narrative mechanisms that are common in dialogues with LLM chatbots. In combination, these mechanisms produce an interactional strategy for…
Measure the Sim-to-Real Gap: Designing an Affordable Real-World Benchmark Platform for Reinforcement Learning in AIoT Systems
arXiv:2607.10309v2 Announce Type: replace Abstract: Reinforcement learning (RL) is commonly employed to enhance the performance of autonomous systems, including the Autonomous Internet of Things (AIoT). However, the…
IndexTTS 2.5 Technical Report
arXiv:2601.03888v5 Announce Type: replace-cross Abstract: In prior work, we introduced IndexTTS 2, a zero-shot neural text-to-speech foundation model comprising two core components: a transformer-based Text-to-Semantic…
Towards Efficient Reasoning in LLM-Based Recommender Systems via Model Merging
arXiv:2608.10447v1 Announce Type: cross Abstract: Large language model-based recommender systems are increasingly adopting slow-thinking models that generate step-by-step reasoning before making predictions, often…
Emotion2Skill: Model-Internal Emotion Signals for Adaptive Skill Selection and Evolution
arXiv:2608.09248v2 Announce Type: replace Abstract: Skill-based LLM agents select reusable procedures from an external library to solve complex tasks, yet their routing decisions rely entirely on text-level signals such…
Evaluation-Conditioned Training: Teaching Models to Generalize to Stronger Oversight Regimes
arXiv:2608.10209v1 Announce Type: new Abstract: Feedback signals used to train Large Language Models (LLMs) are the primary driver of their behavior and our main lever for instilling alignment with human values and…
MemSpec: Memory-Aware Runtime for Adaptive Draft Scheduling in Speculative Decoding on Edge Devices
arXiv:2608.10362v1 Announce Type: cross Abstract: Speculative decoding accelerates autoregressive large language model (LLM) inference by using a lightweight draft model to speculate multiple tokens, reducing expensive…