The Diffusion-Attention Connection
arXiv:2604.09560v2 Announce Type: replace Abstract: Softmax attention is the row-normalized operator of a diffusion map: both normalize a learned score into a Markov operator, and differ only in what the score is…
Daily edition · AI Research
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TILens turns technical updates into a focused daily brief: official releases, trusted reporting, and practitioner analysis, deduplicated and organized by topic.
A Real-Time Tsetlin Machine-based Non-intrusive Load Monitoring System on MCUs
arXiv:2608.18780v1 Announce Type: new Abstract: Non-Intrusive Load Monitoring (NILM) systems estimate individual appliance energy consumption from a single aggregate meter, without requiring separate sensors for each…
On the Power of Source Screening for Learning Shared Feature Extractors
arXiv:2602.16125v3 Announce Type: replace Abstract: Learning with shared representation is widely recognized as an effective way to separate commonalities from heterogeneity across various heterogeneous sources. Most…
Rethinking Privileged Information in On-Policy Self-Distillation
arXiv:2608.18271v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a student on its own responses using token-level supervision from the same model conditioned on privileged reference information.…
Partition the Support, Reconstruct the Residual: Training-Free Sparse Attention for Video Generation and World Models
arXiv:2608.18484v1 Announce Type: cross Abstract: Training-free block-sparse attention can accelerate video transformers, but row-wise attention concentration does not by itself specify an executable sparse operator.…
GigaBrain-WBC-0.5: A Behavior World Model for Robust Whole-Body Control with Environment Interaction
arXiv:2608.18234v1 Announce Type: cross Abstract: Whole-body motion tracking policies turn a humanoid into a robust control interface: the teleoperator---or an upstream model---only supplies a coarse movement intent,…
Cacheable by Design? Training Mixture-of-Experts Routers for Locality Against the Edge Memory-Bandwidth Wall: A Pre-Registered Negative Result with a Systems Measurement Study
arXiv:2608.18261v1 Announce Type: cross Abstract: Serving a 235B-parameter Mixture-of-Experts (MoE) model on a single 8 GB GPU is bottlenecked not by compute but by memory bandwidth: decode must stream each token's…
Approximate Speculative Decoding
arXiv:2608.03447v2 Announce Type: replace Abstract: Speculative decoding accelerates autoregressive generation by verifying a draft block with a target model in parallel. Under standard greedy verification, decoding…
Tianmu-TC: Physics-constraints Generative Artificial Intelligence for Global Tropical Cyclone Forecasting
arXiv:2608.18500v1 Announce Type: new Abstract: Tropical cyclones (TCs) pose severe risks from strong winds and heavy rainfall. However, forecasting their track and intensity remains challenging due to chaotic…
Eyes on the Image: Gaze Supervised Multimodal Learning for Chest X-ray Diagnosis and Report Generation
arXiv:2508.13068v2 Announce Type: replace-cross Abstract: Medical vision-language models still struggle to match radiologists' attention and to verbalize findings with explicit spatial grounding. We address this gap…
Coordination on a Budget: Federated Active Learning with Few Labels
arXiv:2608.18634v1 Announce Type: new Abstract: Federated Active Learning (FAL) addresses the dual challenges of data privacy and label scarcity, where the absence of a global data view introduces additional hurdles for…
Open-MOPD: Diagnosing and Fixing Capability Imbalance in Multi-Teacher On-Policy Distillation
arXiv:2608.19098v1 Announce Type: new Abstract: Multi-teacher on-policy distillation (M-OPD) has emerged as a promising paradigm for consolidating domain-specialized reinforcement learning (RL) experts into a single…
Denoising-Aware Inversion: Revealing Privacy Risks in Noise-Protected Text Embeddings
arXiv:2608.18610v1 Announce Type: new Abstract: Dense text embeddings are widely used in data mining, retrieval, and downstream machine learning systems due to their compact and semantically rich representations, but…
Adaptive Multi-Agent Feature Selection for Personalized Fall Risk Prevention
arXiv:2608.18450v1 Announce Type: new Abstract: Falls among older adults represent a major public health challenge driven by complex, time-varying interactions across multiple risk domains. Effective fall risk factor…
Sobolev Regularized Score Difference Estimation in Diffusion Models
arXiv:2608.18237v1 Announce Type: cross Abstract: Estimating the difference of two Stein's score functions is a fundamental problem in generative modeling. In particular, score differences arise naturally in transfer…
Contrasting Cost-Agnostic and Cost-Sensitive Losses under Limited Model Capacity via $\mathcal H$-consistency
arXiv:2502.19522v2 Announce Type: replace Abstract: There is a prevalent debate in machine learning about whether practitioners should train models to optimize a task-agnostic objective (e.g., cross entropy) or…
FedLNS: Leverage LayerNorm Signature Modeling to Mitigate Adversarial Manipulation in Federated LLMs
arXiv:2608.18736v1 Announce Type: new Abstract: Federated training enables language models to learn from distributed private text, but the server cannot directly verify the local supervision or optimization process that…
MLREF: Efficient Module Reuse for Reward Design in Reinforcement Learning via Large Language Models
arXiv:2608.18827v1 Announce Type: new Abstract: Reward function design remains a bottleneck in reinforcement learning. While large language models (LLMs) have enabled automated reward generation, existing methods…
BERTilda: Explainable Topic Lifecycle Tracking with Split/Merge Detection via Similarity-and-Flow Temporal Graphs
arXiv:2608.18101v1 Announce Type: cross Abstract: Longitudinal text streams exhibit topic birth and death, but also discrete structural reorganizations in which themes split into subtopics or merge into broader…
Geometric Data Perturbation with Noisy-Anchor Alignment for Privacy-Preserving Collaborative Learning
arXiv:2608.18749v1 Announce Type: new Abstract: Geometric Data Perturbation (GDP) enables one-shot, privacy-preserving collaborative learning: each participant applies a distance-preserving transformation to its private…
Simple, Safe, and Overlooked: Reclaiming Sustainable Domain Generalization with Statistical Color Matching
arXiv:2608.18915v1 Announce Type: cross Abstract: Hardware shifts, color variations, and changing patient characteristics between development and deployment routinely break trained medical image classifiers. Existing…
A continually expandable foundation model for brain MRI
arXiv:2608.08319v2 Announce Type: replace-cross Abstract: Brain magnetic resonance imaging (MRI) is central to neuroscience and clinical assessment, but models are commonly developed for individual diseases, populations…
Low-Power, Neuromorphic, Acoustic Anomaly Detection for Persistent Machine Monitoring
arXiv:2608.18341v1 Announce Type: cross Abstract: Persistent acoustic monitoring can detect machine faults without physical contact, but always-on inference is constrained by power, latency, and deployment complexity.…
H$^2$EDL: Hyper Evidential Deep Learning for Hierarchical Classification
arXiv:2608.18185v1 Announce Type: new Abstract: Fine-grained recognition often involves hierarchical label spaces, where a model may be confident about a coarse semantic concept while remaining uncertain among its…
Iterative Flow Matching: Path Correction and Gradual Refinement for Enhanced Generative Modeling
arXiv:2502.16445v4 Announce Type: replace Abstract: Generative models for image generation are now commonly used for a wide variety of applications, ranging from guided image generation for entertainment to solving…
PGFS++: Molecular Property Improvement under Synthesis and Diversity Constraints
arXiv:2608.19121v1 Announce Type: new Abstract: Improving molecular properties, such as drug-likeness or binding affinity, is a recurring task in early-stage drug discovery. However, molecules optimized in an…
Mechanistic Interpretability of Structure-Aware Numerical Reasoning in LLaMA 3.1 8B
arXiv:2608.18419v1 Announce Type: new Abstract: Recent work has shown that large language models (LLMs) exhibit strong numerical sequence modeling capabilities and show promise in time-series prediction. While LLMs…
Dynamic Distribution-Aware Uncertainty Tracking in Vision-Language Representation Learning
arXiv:2608.09011v2 Announce Type: replace Abstract: Uncertainty Quantification (UQ) aims to measure the reliability of model predictions, serving as a critical safeguard for deploying Vision-Language Models (VLMs) in…
Training Chemical Plausibility-Aware Large Language Models for Single-Step Retrosynthesis
arXiv:2608.18940v1 Announce Type: new Abstract: Single-step retrosynthesis is a central component of computer-aided synthesis planning, yet its intrinsically one-to-many nature is poorly captured by single-answer…
Mechanist: AI as a Scientific Instrument for Discovering the Mechanisms of Intelligence
arXiv:2608.12036v2 Announce Type: replace-cross Abstract: AI models have achieved remarkable success across diverse domains, yet the mechanisms underlying their capabilities and the risks they may pose remain poorly…
A Unifying Relational Perspective on Expressive Lottery Tickets
arXiv:2608.18819v1 Announce Type: new Abstract: Graph neural networks (GNNs) are widely used, but how parameter sparsity affects the expressivity of relational (RGNNs) and temporal (TGNNs) variants is poorly understood.…
SCORE: Subject Coordinate Recovery for Label-Free Cross-Subject EEG-to-Image Retrieval
arXiv:2608.19134v1 Announce Type: new Abstract: Accurate visual decoding can reveal how the brain represents visual information and recover perceived content from neural signals such as electroencephalography (EEG),…
Quantum Tensor Network Learning with DMRG
arXiv:2608.18901v1 Announce Type: cross Abstract: Tensor Networks are a relatively new machine learning approach. The architectures proposed initially are inspired by approaches from quantum many-body physics…
Trust as a Field: A Macroscopic Representation for Vehicular Networks
arXiv:2608.18178v1 Announce Type: cross Abstract: Trust assessment is a fundamental component of cooperative and connected vehicle systems. However, existing approaches operate primarily at the level of individual…
Europe's Climate Ambition Under Scrutiny: Evidence from Deep Learning Emission Projections
arXiv:2608.18690v1 Announce Type: new Abstract: The European Union has committed to reducing greenhouse gas emissions 55% below 1990 levels by 2030, but whether current trends are compatible with this ambition remains…
AMPLIFAI: A Multiphase CT Dataset for Benchmarking Clinical Reasoning in LI-RADS Assessment of Liver Lesions
arXiv:2608.14778v2 Announce Type: replace-cross Abstract: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality worldwide, with early detection improving survival from <20% to >70%. The…
Bidirectional representational alignment between biological and artificial neural networks
arXiv:2608.18244v1 Announce Type: new Abstract: Recent work has shown that representational alignment between biological and artificial neural networks is asymmetric: model representations predict neural responses much…
Weak-to-Strong Generalization via Bregman Bias-Variance Decomposition
arXiv:2505.24313v3 Announce Type: replace Abstract: Weak-to-strong generalization (W2SG) is the phenomenon in which a powerful student model, trained on labels produced by a weaker teacher, ultimately outperforms the…
GCNO: Gramian Chebyshev Neural Operator for Physics-Based Compression of Wireless Channels
arXiv:2608.18522v1 Announce Type: cross Abstract: Large antenna arrays allow wireless systems to serve more users and achieve higher data rates, but they also make channel feedback expensive: the receiving device must…
Beyond Trial Averaging: Anchoring Neural and Visual Representations for Few-Repetition Brain-to-Image Retrieval
arXiv:2608.19128v1 Announce Type: new Abstract: Decoding visual information from brain signals probes neural representations and enables neuro-rehabilitation and dream decoding. Recent brain-to-image retrieval…
Vector Symbolic Policy Gradient
arXiv:2608.18404v1 Announce Type: new Abstract: We answer this question with Vector-Symbolic Policy Gradient (VSPG), a discrete-action actor that represents each action by a unit-norm hypervector and scores it by…
Visual-Aware Representation of Web Pages for Machine Learning Applications
arXiv:2608.18727v1 Announce Type: new Abstract: Applying machine learning to web pages is challenging due to the need to interpret HTML together with associated resources and perform rendering to obtain a meaningful…
STAND: Semantic Anchoring Constraint with Dual-Granularity Disambiguation for Remote Sensing Image Change Captioning
arXiv:2604.23309v2 Announce Type: replace-cross Abstract: Remote sensing image change captioning (RSICC) aims to describe the difference between two remote sensing images. While recent methods have explored video…
DART-SD: Diamond-topology Aware Retrieval and Tuning for Self-Distillation of Multi-Turn Tool-Calling Agents
arXiv:2608.18524v1 Announce Type: cross Abstract: Equipping Large Language Models (LLMs) with multi-turn tool-calling capabilities is essential for building autonomous agents. However, progress is fundamentally limited…
Reinforced Planning with Latent World Models
arXiv:2608.18669v1 Announce Type: new Abstract: Humans solve complex problems by constructing plans and mentally simulating their outcomes with an internal model of the world. Machine learning has produced world models…
Primitive Representation Learning for Unsupervised Dynamic Contrast Enhanced MRI Reconstruction
arXiv:2608.18055v2 Announce Type: replace-cross Abstract: Reliable quantitative analysis of dynamic contrast-enhanced MRI requires high-quality spatiotemporal reconstructions at high undersampling rates. Scan-specific…
Discretizing Continuous Time Series for Imputation with Masked Diffusion Training
arXiv:2608.19119v1 Announce Type: new Abstract: Time series imputation is a crucial area for reliable time series analysis, yet it remains challenging due to the complex temporal dynamics and noise of real-world data.…
Fair Multi-View Determinantal Coresets via Adaptive NEPv
arXiv:2608.18181v1 Announce Type: cross Abstract: Selecting a small, diverse subset from a large candidate pool often means balancing several incompatible notions of diversity. In trademark curation, for instance, a…
A Comprehensive Review of Large Language Models for Nanophotonics: From Surrogate Modeling to Autonomous Design
arXiv:2608.18279v1 Announce Type: cross Abstract: Metasurfaces have revolutionized the development of photonic devices by enabling unprecedented precision in light manipulation. However, their design processes are often…
ChiroEcho: extending automated bat vocalisation classification beyond the learned taxonomy
arXiv:2608.18191v1 Announce Type: new Abstract: Bats are key indicators of ecosystem health and are protected throughout Europe, making reliable population monitoring a conservation priority. Their cryptic nocturnal…
Seasonal false alarms in customer churn and decline early-warning systems: adjacent-window labels confound seasonality with decline, and a year-over-year correction
arXiv:2608.18174v1 Announce Type: cross Abstract: Customer decline early-warning systems feed account-manager action lists, and every flagged account consumes intervention capacity. In a deployed business-to-business…
The Road Taken: The Role of Optimizers at the Edge of Stability
arXiv:2608.18415v1 Announce Type: new Abstract: The edge of stability refers to a phenomenon in deep learning with gradient-based optimizers where the Hessian eigenvalues of the loss remain stable above a threshold that…
WhiteMatter: All-to-All Cross-Layer Connections via KV Mixing
arXiv:2608.18486v1 Announce Type: cross Abstract: In a Transformer, each layer attends to past tokens only through KV produced at its own depth, despite the presence of deeper representations during autoregressive…
LLM-Powered Predictive Decision-Making for Sustainable Data Center Operations
arXiv:2608.18503v1 Announce Type: new Abstract: The growing demand for AI-driven workloads, particularly from Large Language Models (LLMs), has raised concerns about the significant energy and resource consumption in…
Role-Conditioned Sub-Token Routing for Efficient Vision-Language-Action Policies
arXiv:2608.18410v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models process long multimodal token sequences, making inference expensive in both memory and computation. Existing efficiency methods mainly…
Preference Reasoning under Indeterminacy in Large Language Models
arXiv:2608.18631v1 Announce Type: cross Abstract: As large language models evolve into decision-making agents, the ability to reason over preferences becomes fundamental to alignment, coordination, and collective…
Monroe: A Molecular Foundation Model for In-Context Probabilistic Inference
arXiv:2608.18982v1 Announce Type: new Abstract: Bioassay activity prediction is often data-limited because drug-discovery datasets rely on time-consuming and expensive wet-lab experiments for data generation and…
Safe Domain Adaptation for Physics: Overcoming Nuisances, Label Shifts, and Simulation Priors
arXiv:2608.18190v1 Announce Type: new Abstract: Domain adaptation is widely used to make neural networks trained on simulations applicable to experimental data. Its premise is that the two domains differ only in…
On the Slow Convergence to Trivial Solutions of Algorithms for Hard Optimization Problems
arXiv:2608.18910v1 Announce Type: new Abstract: Hard combinatorial optimization problems, many of which are NP-hard, present fundamental algorithmic challenges. Average-case analysis on random instances has emerged as a…
Entropy-Constrained Adaptive Stochastic Quantization
arXiv:2608.18147v1 Announce Type: new Abstract: Adaptive stochastic quantization (ASQ) is a recently introduced quantization approach that optimizes the Mean Squared Error (MSE) for a given input while preserving…
Online Learning for Dynamic Constellation Topologies
arXiv:2603.25954v2 Announce Type: replace Abstract: The use of satellite networks has increased significantly in recent years due to their advantages over purely terrestrial systems, such as higher availability and…
MIFR: A Modality-Invariant and Fair Representation Framework for Skin Disease Classification
arXiv:2608.18774v1 Announce Type: cross Abstract: Skin diseases represent a major global public health burden, yet machine learning tools developed to assist in their diagnosis suffer from two critical limitations:…
ERASE: EaRly bAckpropagation SchEdule for Faster Training of Modern Recommendation Systems
arXiv:2608.18469v1 Announce Type: new Abstract: Lightweight proxy models enable rapid experimentation without repeatedly training frontier-scale systems, but their small kernels often leave modern accelerators…
Online Bipartite Matching with Reusable Capacity under Non-Stationary Rewards
arXiv:2608.18130v1 Announce Type: cross Abstract: We study online bipartite matching with reusable server capacity and non-stationary rewards. Jobs arrive sequentially, reveal compatible servers, reward rates, and…
Beyond Predictive Fairness: Quantifying Attribution Consistency Across Demographic Groups in Diabetic Retinopathy Screening
arXiv:2608.18759v1 Announce Type: new Abstract: Fairness in medical imaging is commonly evaluated through subgroup performance metrics, yet it remains unclear whether models rely on consistent visual evidence across…
Towards Lightweight Reliability: Using Soft Prompts for Hallucination Mitigation in Large Language Models
arXiv:2606.00919v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have seen widespread adoption across various domains, yet their reliability is frequently undermined by hallucinations - responses…
Hallucination Detection in Large Language Models Using Diversion Decoding
arXiv:2607.10476v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have emerged as a powerful tool for retrieving knowledge through seamless, human-like interactions. Despite their advanced text…
Performance Drift Detection in Machine Learning as a Service (MLaaS) for IoT Environments
arXiv:2608.18555v1 Announce Type: new Abstract: Machine Learning as a Service (MLaaS) is a powerful cloud paradigm enabling data-driven intelligent applications in Internet of Things (IoT) environments, widely adopted…
GQ-FSL: Green Quantized Federated Split Learning Framework for Wireless Edge Networks
arXiv:2607.29659v2 Announce Type: replace Abstract: Deploying state-of-the-art deep neural networks (DNNs) at the wireless edge is severely bottlenecked by the strict energy and resource constraints of mobile devices.…
A Configuration-First Framework for Reproducible, Low-Code Machine Learning: a Localization Use Case
arXiv:2510.25692v5 Announce Type: replace-cross Abstract: As machine learning underpins more critical applications, the value of a reported result depends on whether it can be compared and repeated. In practice, this…
Diffusion Models for High-Dimensional Clustered Data: Intrinsic-Dimension Adaptivity via Bayesian Classification
arXiv:2608.19067v1 Announce Type: cross Abstract: The empirical success of diffusion models in generative modelling has motivated theoretical work, including quantitative error bounds and qualitative analyses that…
Multi-Objective Optimization Under Uncertainty of Part Quality in Fused Filament Fabrication
arXiv:2608.18429v1 Announce Type: cross Abstract: This work presents a data-driven methodology for multi-objective optimization under uncertainty of process parameters in the fused filament fabrication (FFF) process.…
LionMuon: Alternating Spectral and Sign Descent for Efficient Training
arXiv:2605.19811v3 Announce Type: replace Abstract: In large-scale optimization, the cheapness and effectiveness of update steps are the most crucial factors for a successful optimizer. Sign-based optimizers like Lion…
Change Point--Aware Evaluation and Re-Calibration of PPG-Based Blood Pressure Estimation
arXiv:2608.18639v1 Announce Type: cross Abstract: Non-invasive continuous blood pressure (BP) monitoring using photoplethysmography (PPG) is a promising alternative to cuff-based measurements. However, existing…
Residual Algebra for Representation-Preserving Learning
arXiv:2608.07349v2 Announce Type: replace Abstract: Learning from heterogeneous representations is often reduced to feature concatenation, erasing which representation produced each error. We propose residual algebra,…
Stability-Aware Feature Design for Robust Watermark Detection in Machine-Generated Text
arXiv:2608.18102v1 Announce Type: cross Abstract: The widespread adoption of large language models (LLMs) has intensified the demand for principled methods to distinguish human from machine-generated text. Watermarking…
Transportable Causal Effect Estimation across Networks under Interference
arXiv:2608.18932v1 Announce Type: new Abstract: Estimating causal effects under network interference typically assumes that the network used for training and the network used for deployment coincide. In practice, an…
SHANG++: Robust Stochastic Acceleration under Multiplicative Noise
arXiv:2603.09355v2 Announce Type: replace-cross Abstract: Under the multiplicative noise scaling (MNS) condition, original Nesterov acceleration is provably sensitive to noise and may diverge when gradient noise…
Many Optimizers But Only One Training Path: Repeated Resampling for Adaptive Optimizer Selection
arXiv:2608.18810v1 Announce Type: new Abstract: An optimizer is usually chosen before training a deep neural network and then kept fixed. Treating optimizer choice as a hyperparameter could boost performance, but it…
Mask2Real-WM: Segmentation Masks as a Sim-to-Real Bridge for Controllable Dexterous World Models
arXiv:2607.04546v2 Announce Type: replace-cross Abstract: Action-conditioned world models allow robots to predict the future consequences of candidate actions without additional physical interaction, supporting policy…
Pretraining Reusable Inference Across Views with Synthetic Task Priors
arXiv:2608.19115v1 Announce Type: new Abstract: Modern pretrained encoders make representations from heterogeneous views increasingly reusable, but the procedure that determines view utility and combines evidence is…
The Embodiment Gap in Robot Foundation Models
arXiv:2608.18433v1 Announce Type: cross Abstract: Robot foundation models (RFMs), including vision-language-action (VLA) policies, are often discussed through a scaling view: more data, larger models, and broader…
Beyond receptive fields: sequence-pooled normalization can supply most of a sequence labeler's context
arXiv:2608.18576v1 Announce Type: new Abstract: A convolutional sequence labeler's receptive field is routinely treated as the extent of the model's usable context: it sets dilation schedules, bounds streaming horizons,…
Bound-Aware Per-Organ Recall Risk Control for Multi-Organ CT Segmentation under Clinical Domain Shift
arXiv:2608.18193v1 Announce Type: cross Abstract: Distribution-free risk control adds organ-specific recall guarantees to frozen segmentation. We calibrate per-organ thresholds for an AMOS-trained nnU-Net, audit…
MAVEN: A Macro-Societal Value Evaluation Framework of Multimodal Content with Compact Aligned Evaluators
arXiv:2608.18096v1 Announce Type: cross Abstract: Assessing whether multimodal content aligns with macro-societal values, such as peace, justice, and freedom, has become an increasingly urgent challenge. Existing…
Hybrid LLM-Augmented Reinforcement Learning Agents for Complex Sequential Decision Tasks
arXiv:2608.03502v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have recently shown strong capabilities in reasoning, planning, and tool-use, enabling new forms of autonomous agents. However,…
Leaf Values as Coordinates: Exact Contrastive Explanation for Gradient-Boosted Ensembles
arXiv:2608.19127v1 Announce Type: new Abstract: A gradient-boosted ensemble predicts by summing one leaf value per tree. Read those values as coordinates rather than as intermediate results, and every instance becomes a…
Measuring the Dependency Gap: Diagnosing Inter-Column Fidelity in Tabular Generative Models
arXiv:2607.21636v4 Announce Type: replace Abstract: Synthetic tabular data are valued for preserving not just column-wise marginals but inter-column dependency. Yet the most commonly reported certification score, a…
Understanding Multilingual Medical ASR Adaptation Through Layer-Wise Analysis
arXiv:2608.18825v1 Announce Type: cross Abstract: Medical automatic speech recognition (MedASR) requires adaptation to specialised terminology, limited annotated clinical data, and multilingual use cases. Although…
Physics-Unrolled Neural Operator for Wireless Field Modeling
arXiv:2608.18495v1 Announce Type: new Abstract: Radio maps are essential for wireless decision-making tasks such as access-point placement, coverage planning, and localization, but their fine spatial details are…
Fast Best-in-Class Regret for Contextual Bandits
arXiv:2510.15483v3 Announce Type: replace-cross Abstract: We study the problem of stochastic contextual bandits in the agnostic setting, where the goal is to compete with the best policy in a given class without…
Graphical Design of Interpretable Architectures
arXiv:2608.18936v1 Announce Type: new Abstract: Designing, implementing, and comparing interpretable architectures requires a formal language to represent them. The most common representations fall short in one of two…
Whole-Piece Training for Symbolic Music Language Models via Full-Horizon Compressed Recurrence
arXiv:2602.19816v3 Announce Type: replace-cross Abstract: For computational efficiency, modern language models are typically trained on independently sampled fixed-length sequences. Symbolic music language models…
Scalable Geospatial Machine Learning for Power-Line Asset Risk: Integrating Remote Sensing for Lightning and Vegetation Risk Modelling
arXiv:2608.18611v1 Announce Type: new Abstract: Electric power networks are increasingly exposed to weather-sensitive failure mechanisms that require asset-level, spatially explicit risk modelling for effective…
Geometric Iterative Retrieval for Neural Audio Codec Resynthesis
arXiv:2608.19141v1 Announce Type: cross Abstract: Neural audio codecs based on Residual Vector Quantization (RVQ) have become the dominant discrete representation for token-based general audio generation, yet…
Structured Latent Space Modeling over Multi-Scale Temporal Patches for Multivariate Time Series Forecasting
arXiv:2607.19404v2 Announce Type: replace Abstract: Existing patching and multi-scale methods advance multivariate time series forecasting but treat learned representations as transient byproducts of prediction, lacking…
StocksTalk: A Voice-Enabled Conversational Agent for Structured Query Generation over Web Data
arXiv:2608.18105v1 Announce Type: cross Abstract: StocksTalk is a voice-enabled conversational system for transforming spoken financial screening requests into executable and validated structured queries over real-world…
Conformal Policy Control
arXiv:2603.02196v4 Announce Type: replace-cross Abstract: An agent must try new behaviors to explore and improve. In high-stakes environments, an agent that violates safety constraints may cause harm and must be taken…
Regularised Iterative Generalised Least Squares with Optimal Selection of the Hyper-Parameter for Identifying Nonlinear Phenomenological Models
arXiv:2608.18742v1 Announce Type: cross Abstract: In some fields currently dominated by empirical approaches, such as state of health (SoH) prediction for lithium-ion batteries, phenomenological models motivated by…
Task-Conditioned Least-Privilege Learning for Executable Terminal and MCP Agents
arXiv:2608.18351v1 Announce Type: cross Abstract: Tool-using large language-model agents can complete a task while exercising authority that the user did not grant or the task does not need, causing excess-authority…
Compress and Forget: bitsandbytes Quantization Amplifies Proactive Interference in LLMs
arXiv:2608.18578v1 Announce Type: cross Abstract: Proactive interference (PI) is a documented failure mode in large language models in which retrieval of a repeatedly overwritten value degrades as prior overwrites…
MotoSafety: Edge-AI with Learned Temporal Importance for Two-Wheeler Collision Risk Assessment Under Time Pressure
arXiv:2608.17823v2 Announce Type: replace Abstract: Powered two-wheeler riders face critical safety challenges in low- and middle-income countries, yet limited studies exist on how cognitive stressors such as Time…
Redakto - The Incognito Tab for LLMs
arXiv:2608.18260v1 Announce Type: cross Abstract: Large Language Models (LLMs) are being increasingly used in everyday applications. A major challenge in the context of LLMs or Artificial Intelligence (AI) in general is…
Forgetting, plasticity, and co-observation: a third facet of continual learning
arXiv:2608.18803v1 Announce Type: new Abstract: Efficient continual learning remains a fundamental challenge for deep neural networks. While catastrophic forgetting and loss of plasticity are widely considered the…
Visual-Prompt Guided Wildlife Instance-Level Recognition
arXiv:2608.18246v1 Announce Type: cross Abstract: Fine-grained wildlife re-identification remains a challenging area in research. Current state-of-the-art approaches apply a detection and re-identification pipeline. We…
Topology-Aware Differential Privacy in Hierarchical Federated Learning
arXiv:2506.19260v3 Announce Type: replace-cross Abstract: Hierarchical federated learning places regional aggregators between clients and the cloud, so a participant's update is observed only alongside its neighbours'.…
Cross-Cohort Spectral-Temporal Dissociation in Frozen EEG Foundation-Model Representations
arXiv:2607.24834v3 Announce Type: replace-cross Abstract: Objective. We tested whether frozen representations from five EEG foundation models support decoding of long-range temporal correlations, measured as the…
A Critical Synthesis of Uncertainty Quantification and Foundation Models for Semantic Segmentation
arXiv:2608.18709v1 Announce Type: cross Abstract: Foundation models are increasingly breaking what seemed to be impossible not long ago by enabling unprecedented accuracy and cross-domain generalization. Yet their lack…
Towards Reversible Forgetting: Managing Obsolete Knowledge in Continual Enterprise AI Agents
arXiv:2608.18177v1 Announce Type: new Abstract: Continual learning has traditionally treated forgetting as a failure, emphasizing preservation of previously acquired knowledge as environments evolve. We argue that this…
Flama: a Python framework for development and deployment of production-ready APIs, machine learning, and LLM services
arXiv:2608.18733v1 Announce Type: cross Abstract: We present Flama, an open-source Python framework for developing and deploying production-ready web APIs, machine learning services, and large-language-model (LLM)…
The Impact of CutMix on Reliability and Robustness in Semantic Segmentation
arXiv:2608.18715v1 Announce Type: cross Abstract: Ensuring not only high accuracy but also reliable and robust predictions is critical for the deployment of semantic segmentation models in safety-critical applications…
Beyond Teacher Likelihood: Group-Calibrated On-Policy Distillation for Long-Context Reasoning
arXiv:2608.19181v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own responses using dense token-level guidance from a stronger teacher. In long-context tasks, however, token-level…
SIGMA: Symmetry-aware, Intelligent, Geometric, Multi-objective Adaptive Control for Robust, Dependable Traffic Management
arXiv:2608.18263v1 Announce Type: new Abstract: Traffic signal control is a complex sequential decision-making problem requiring real-time adaptation and trade-offs among throughput, delay fairness, signal stability,…
Enhancing EBSD throughput of battery electrode materials using super-resolution generative adversarial networks
arXiv:2608.19117v1 Announce Type: new Abstract: Quantitative microstructural characterization of Li-ion battery electrode materials using electron backscatter diffraction (EBSD) has been proven as a critical method for…
Atrial Fibrillation Detection with Arbitrary Leads via a Codebook-Based Reconstruction-Classification Framework
arXiv:2608.18451v1 Announce Type: new Abstract: \textbf{Background and Objective}: Reliable atrial fibrillation (AF) detection from electrocardiogram (ECG) signals remains challenging in real-world clinical settings due…
Sharp Capacity Thresholds in Linear Associative Memory: From Top-1 Retrieval to Tail-Average Learning
arXiv:2605.05189v2 Announce Type: replace-cross Abstract: How many key-value associations can a $d\times d$ linear memory store? The answer depends not only on the $d^2$ degrees of freedom in the memory matrix, but also…
Lost in Aggregation: How Benchmarks Overlook Irreplaceable Model Strengths
arXiv:2608.18919v1 Announce Type: new Abstract: Tabular machine learning benchmarks typically summarize performance by averaging scores, ranks, or pairwise wins across datasets. Such aggregates are useful for selecting…
RouteCost: A Production-Inspired Multi-Stage Framework for Pre-Order Shipping Cost Estimation in E-Commerce
arXiv:2607.16230v2 Announce Type: replace Abstract: Accurate pre-order shipping cost estimation is important in e-commerce because it affects price presentation, margin planning, and conversion. In practice, shipping…
SPK: Eliciting Structured Prior Knowledge for Interpretable Out-of-Distribution Detection in Real-Time Object Detection
arXiv:2608.19080v1 Announce Type: cross Abstract: Object detectors often produce over-confident predictions for objects outside their training categories, leading to so-called out-of-distribution (OoD) hallucinations.…
Sharper Regret Bounds for Time-Varying Gaussian Process Bandits with Constant Exploration
arXiv:2608.18863v1 Announce Type: cross Abstract: We study Bayesian optimization in a time-varying environment where the unknown reward function evolves according to a Gaussian process drift model. Existing GP-UCB…
Does Mapping Non-Maximal Probabilities to GMM Components Matter for S-JEPA Encoder Representations?
arXiv:2608.19084v1 Announce Type: new Abstract: S-JEPA uses soft Gaussian mixture model (GMM) posteriors instead of hard cluster labels to preserve uncertainty. It remains unclear whether the probability values alone…
What Makes Software Issue Resolution Tasks Difficult for Agents?
arXiv:2608.18280v1 Announce Type: cross Abstract: Background. Advances in agentic systems are simultaneously, and rapidly, saturating benchmarks. Despite this often discussed phenomena, benchmark scores remain difficult…
ProxyGuard: Direct Reliability Inference for Randomized Data Release Mechanisms with Shared Targets
arXiv:2608.18643v1 Announce Type: new Abstract: Researchers often choose a proxy dataset from many releases, transformations, or seeds. Search can make an invalid release appear adequate, while one adequate release does…
Gradient Mirage: Trainable yet Label-Unidentifiable Gradients in Large Language Model Split Learning
arXiv:2608.18767v1 Announce Type: cross Abstract: Gradient matching attacks (GMAs) in LLM split learning (SL) rely on a critical yet underexplored assumption: the gradient exposed at the split interface is a faithful…
GEAR: Generative Expansion and Real Anchoring for Two-Stage Distillation of Tabular Foundation Models
arXiv:2608.18849v1 Announce Type: new Abstract: Tabular foundation models (TFMs) achieve strong performance through in-context learning, but context-dependent inference imposes substantial latency and memory costs,…
A systematic review of machine learning techniques to address diagnosis and treatment of autism: challenges and opportunities
arXiv:2608.18188v1 Announce Type: new Abstract: Autism spectrum disorder (ASD) is a developmental disability characterized by challenges in social interaction and communication. As the causes of ASD remain unclear,…
Off-Manifold Collapse in Guided Protein Language Models
arXiv:2608.18597v1 Announce Type: new Abstract: Protein language models are widely used priors for protein sequence design, and a growing body of work controls them at inference time as an alternative to fine-tuning.…
Selection, Recombination, or a Fresh Solve? A Candidate-Free Control for Single-Pass Test-Time Aggregation
arXiv:2608.18379v1 Announce Type: new Abstract: When every candidate is wrong, correct-candidate selection is unavailable, yet the aggregation call can still solve the problem afresh. A correct aggregate answer may…
Pedagogical AI in Mental Health: A Tri-Stream Fine-Tuned LLM Framework for Automated Clinical Supervision and Risk Triage
arXiv:2608.18438v1 Announce Type: cross Abstract: Modern mental healthcare faces a critical shortage of senior supervisory oversight, leading to a "supervision gap" where novice therapists manage high-stakes risks with…
Position: Current Model Cards Are Insufficient for Downstream Governance of Open-Weight Foundation Models
arXiv:2608.18086v1 Announce Type: cross Abstract: The growth of open-weight foundation models (OWFMs) has prompted the AI community to re-evaluate strategies for effective downstream governance. Although model cards…
Jailbreaking in the Haystack
arXiv:2511.04707v2 Announce Type: replace-cross Abstract: Recent advances in long-context language models (LMs) have enabled million-token inputs, expanding their capabilities across complex tasks like computer-use…
LLM-Driven AutoML for Cross-Lingual Handwritten OCR: Closed-Loop Neural Architecture Search with GPT-5, GPT-4o, and Claude Sonnet 4
arXiv:2607.15509v3 Announce Type: replace-cross Abstract: We present a fully automated closed-loop AutoML framework that uses GPT-5, GPT-4o, and Claude Sonnet 4 as autonomous neural architecture designers for…
A single design choice determines whether machine learning models of materials make physically impossible predictions
arXiv:2608.18714v1 Announce Type: cross Abstract: Machine-learned models are replacing first-principles calculations across materials discovery, and physical symmetry is the central guarantee built into them. The debate…
Looped Language Models Improve Compositional Tool Calling
arXiv:2608.18171v1 Announce Type: cross Abstract: Looped language models have shown promising results on reasoning benchmarks, yet their potential for agentic tool use remains largely unexplored. We study this question…
Matching Accuracy, Different Geometry: Evolution Strategies vs GRPO in LLM Post-Training
arXiv:2604.01499v3 Announce Type: replace Abstract: Evolution Strategies (ES) have emerged as a scalable gradient-free alternative to reinforcement learning based LLM fine-tuning, but it remains unclear whether…
Optimizing Energy Efficiency and Grid Stability via Public EV Charging Flexibility
arXiv:2608.18126v1 Announce Type: cross Abstract: This study evaluates the potential of electric vehicle (EV) charging flexibility to enhance both energy efficiency and power grid stability. Using real-world data from…
On the Robustness of Vision-Language Models in Zero-shot Privacy Classification
arXiv:2510.09253v2 Announce Type: replace-cross Abstract: Automatic systems for document understanding require multimodal models that accurately identify sensitive visual content, even in the presence of image…
GraphK: Variable-Size Graph Generation with Efficient Edge Construction
arXiv:2608.18777v1 Announce Type: new Abstract: Graph generation models have advanced significantly with deep learning, yet they remain limited in scalability, flexibility, and ability to model underlying structures. We…
Score the Algebra, Not the Span: Dimension Reduction for Transfer Operator Models of Dynamical Systems
arXiv:2608.18918v1 Announce Type: new Abstract: Dimension reduction for dynamical systems is standard practice, and the standard route is spectral: model the transfer (Koopman) operator by its leading modes. We show…
What Can Artificial Intelligence Learn from Medicine? Generative Analogies and Reliable Machine Learning Systems
arXiv:2608.18186v1 Announce Type: new Abstract: In the past few years, machine learning (ML) has been widely (and to an extent, successfully) implemented in medicine. However, uncertainties surrounding ML have made it…
From Inference to Adaptation: A Unified Optimal Transport View of Vision Language Model
arXiv:2608.18339v1 Announce Type: cross Abstract: Vision-language models (VLMs) have demonstrated remarkable zero-shot capabilities yet remain sensitive to real-world distribution shifts during inference. Although…
Allocating Recurrent Compute in Looped Language Models
arXiv:2608.18230v1 Announce Type: new Abstract: Looped language models improve reasoning and knowledge manipulation by applying shared computation repeatedly. Existing systems usually repeat an entire layer stack,…
NanoSleep: A Parameter-Efficient Hybrid Temporal Convolutional Network for Single-Channel Sleep Stage Classification
arXiv:2608.18571v1 Announce Type: new Abstract: Sleep stage classification from single-channel electroencephalography (EEG) is essential for wearable and home-based sleep monitoring. However, many deep learning models…
Tensor Field Models
arXiv:2608.18808v1 Announce Type: new Abstract: This paper introduces Tensor Field Models (TFMs), realization-level Mathematical Structures in which a learned Operator maps a product of admissible component-section…
DeGLIF for Label Noise Robust Node Classification using GNNs
arXiv:2506.00244v2 Announce Type: replace Abstract: Noisy labelled datasets are generally inexpensive compared to clean labelled datasets, and the same is true for graph data. In this paper, we propose a denoising…
SkillNet: Create, Evaluate, and Connect AI Skills
arXiv:2603.04448v2 Announce Type: replace-cross Abstract: Current AI agents can flexibly invoke tools and execute complex tasks, yet their long-term advancement is hindered by the lack of systematic accumulation and…
A Cloud-Edge System for Multimodal Clinical Screening in Resource-Constrained Rural Settings
arXiv:2608.12745v2 Announce Type: replace Abstract: Medical AI has demonstrated specialist-level diagnostic accuracy, yet these capabilities remain largely inaccessible in resource-constrained rural settings where…
A Remote Approach to Cashew Orchard Detection: Leveraging Active Learning with Satellite Imagery in Guinea-Bissau
arXiv:2608.11996v2 Announce Type: replace-cross Abstract: Cashew production is a widespread economic activity in Guinea-Bissau, as well as other countries in West Africa. However, unregulated cashew production can be…
Learning Topological Features of $\widehat Z$-invariants
arXiv:2608.18570v1 Announce Type: cross Abstract: Machine learning and data analysis techniques have recently emerged as powerful tools for identifying patterns and formulating conjectures in mathematical research, most…
Robust Risk Under Evolving Uncertainty: A Wasserstein Counterpart of the Entropic Value-at-Risk
arXiv:2608.19073v1 Announce Type: cross Abstract: An agent still learning its environment should be cautious while ignorant and bold once confident. The entropic value-at-risk captures this through a robust-optimization…
Flux-form spatiotemporal neural operators for coarse-grained dynamics of multiscale PDEs
arXiv:2608.18148v1 Announce Type: cross Abstract: We study data-driven prediction of coarse-grained dynamics in multiscale PDE systems. Adopting a closure-free operator-learning viewpoint, we apply a linear…
Progressive Experience Fusion for Multi-Task World Model Control in Endovascular Navigation
arXiv:2608.18647v1 Announce Type: cross Abstract: Autonomous endovascular navigation could support the delivery of mechanical thrombectomy to underserved areas, but controllers must navigate long, multi-stage paths…
Pre-Training for Simulation-Based Science: A Study on Jet Foundation Model Training Objectives
arXiv:2606.14870v2 Announce Type: replace-cross Abstract: Foundation models (FMs) trained on large datasets and fine-tuned on downstream tasks have emerged as a powerful paradigm in AI for science. Industrial FMs are…
MorphoGP: A Nonparametric Framework for Predicting Equilibrium Beach Profiles Under Tidal Influence
arXiv:2608.18558v1 Announce Type: new Abstract: The prediction of equilibrium beach profiles under tidal influence is of fundamental importance for sustainable coastal development, informing shoreline protection…
From Storage to Access: Verifiable Activation of Parametric Knowledge in LLMs via Explicit Priming and Implicit Reasoning
arXiv:2608.18581v1 Announce Type: cross Abstract: Although Large Language Models (LLMs) encode rich factual knowledge in their parameters, reliably recalling and verifying such knowledge remains a key bottleneck in…
Rethinking Self-Evolution: A Constrained Exploration-Exploitation Process for Mitigating Skill Overfitting
arXiv:2607.26643v2 Announce Type: replace-cross Abstract: Enabling large language model (LLM) agents to accumulate and reuse experience from past interactions remains a central challenge in real-world applications. A…
Which Negatives Matter? Ask Your Text Encoder: Adaptive Similarity Margins for Dense-Caption Retrieval
arXiv:2608.18521v1 Announce Type: cross Abstract: Dense-caption retrieval has recently been improved by introducing segmentation, edge maps, LLM-filtered captions, and cross-modal modules into contrastive fine-tuning.…
A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression
arXiv:2608.11917v2 Announce Type: replace Abstract: Multi-output Gaussian process regression scales cubically in the number of observations times outputs, and dense kernel-matrix methods need bespoke handling whenever…
Graph-Based Approaches to Learning Epileptogenic Zone Localization Using Stereo-EEG Recordings
arXiv:2608.18887v1 Announce Type: new Abstract: The epileptogenic zone (EZ) is the brain region that generates seizures in an individual, and is the target of epilepsy surgery. Localizing the EZ from stereo-EEG (sEEG)…
Global Crises and National Policies: A Large Scale Analysis of Political Content in German Language Online Media
arXiv:2608.18268v1 Announce Type: cross Abstract: Today most media content is consumed based on algorithmic recommendations. Evidence suggests that this can lead to politically biased media consumption patterns.…
MARCUS: Missing-Aware Region Representation with Contextual Urban Signals for Rent Prediction
arXiv:2608.18546v1 Announce Type: new Abstract: Multimodal urban data has expanded the applications of urban region representation learning, such as functional zone identification and real estate appraisal, but also…
How Quantum Is the Advantage? A Fair, Calibration- and Noise-Aware Benchmark and Attribution Audit of Quantum Machine Learning for Network Intrusion Detection
arXiv:2608.18155v1 Announce Type: cross Abstract: Quantum machine learning (QML) for network intrusion detection (NIDS) is routinely reported to reach near-perfect accuracy, yet the most rigorous studies find that…
SingularClip: Preventing Spectral Collapse to Maintain Plasticity in Continual and Reinforcement Learning
arXiv:2608.18319v1 Announce Type: new Abstract: Neural networks trained on nonstationary tasks frequently lose the ability to fit new targets, a phenomenon referred to as loss of plasticity. We identify a novel source…
Decision-Metric Alignment in Latent World Models: Diagnostics and Action-Conditioned Objectives for MPC Planning
arXiv:2608.18746v1 Announce Type: new Abstract: JEPA-style latent world models can use Euclidean distance to a goal latent as the cost for model-predictive control (MPC). Strong decoding of task variables, however, does…
Continual Reasoning Gym: Diagnosing and Harnessing Shared Reasoning in Continual RLVR
arXiv:2608.18574v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) commonly post-trains reasoning models on multiple tasks, while rerunning multitask RLVR (MTRL) as new tasks are added…
Enhancing Distance-Based Graph Autoencoders with Structural Penalties for Dynamic Graph Embedding
arXiv:2608.18762v1 Announce Type: new Abstract: Graph autoencoders (GAEs) are widely used for learning representations of dynamic graphs. However, their optimisation objectives typically do not take structural…
Debiased Inference for AI-Generated Data without Gold-Standard Labels: Identification via Multiple Imperfect Measurements
arXiv:2608.18294v1 Announce Type: cross Abstract: An increasing number of scholars use AI to measure variables they subsequently include in downstream analyses. Although AI-measured variables are often analyzed as if…
A FEM-Based Surrogate Modelling and Optimization Framework for Physics-Constrained Electromagnetic Coil Design
arXiv:2608.18903v1 Announce Type: new Abstract: This work evaluates surrogate-assisted optimization of a seven-parameter current-excited coil--core benchmark subject to geometric, manufacturing, and separate core and…
Learned, Then Lost: A Measured Single-Example Counterfactual in Pre-training
arXiv:2608.19168v1 Announce Type: new Abstract: A single training example's contribution to a finished model is normally estimated rather than measured, because measuring it takes two expensive full pre-training runs…
FedCoRe: Target-Adaptive Completion for Missing Modalities in Healthcare Federated Learning
arXiv:2608.18311v1 Announce Type: cross Abstract: Federated multimodal models often assume every site has every modality, although hospitals differ in access to EHRs, chest radiographs, and ECGs. We study this setting…
Algorithms for adaptive and heteroskedastic linear regression at the computational threshold
arXiv:2608.18402v1 Announce Type: cross Abstract: We study finite-sample linear regression in the presence of varied and unknown label noise, focusing on the heteroskedastic and adaptive linear regression models.…
Infrared Universality of Collective Dynamics across Transformer and State-Space Architectures
arXiv:2608.18592v1 Announce Type: new Abstract: Whether distinct neural architectures develop common collective dynamics remains an open question. Recent analysis of Transformer language models revealed a nearly flat,…
Inference and Uncertainty Quantification for Streaming $r$-PCA
arXiv:2608.18374v1 Announce Type: cross Abstract: We address two open questions in streaming PCA via Oja's algorithm: sharp operator-norm convergence for general rank under sub-Gaussian data, and distributional…
Learning Canonical Register Automata over Ordered Data Domains
arXiv:2608.18765v1 Announce Type: cross Abstract: Register automata are finite automata equipped with memory that recognize data languages over infinite alphabets. In this work, we investigate active learning algorithms…
An Empirical Benchmark of Deep Time-Series Models for Smart Meter Energy Forecasting
arXiv:2608.18675v1 Announce Type: new Abstract: Accurate forecasting of energy consumption is important for the efficient operation of power systems, with direct implications for operational costs, energy management,…
AutoOR: Scalably Post-training LLMs to Autoformalize Operations Research Problems
arXiv:2604.16804v3 Announce Type: replace Abstract: Optimization problems are central to decision-making in manufacturing, logistics, scheduling, and other industrial settings. Translating complicated descriptions of…
Multi-Agent Off-Policy Deep Reinforcement Learning for Smart Campus Coverage
arXiv:2608.19049v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) has recently gained a great attention due to its real-time adaptation and effectiveness in complex optimization problems. This paper…
ClosureBench: A Constructive Benchmark for Compositional Graph Reasoning
arXiv:2608.18242v1 Announce Type: new Abstract: We introduce ClosureBench, a constructive benchmark for compositional graph-relational reasoning with programmatically verified ground truth. Unlike fixed-test-set…
To Go Far, Go Together: Diverse Preferences Induce a Curriculum for Reward Optimization
arXiv:2608.18770v1 Announce Type: new Abstract: Learning a reward model from human feedback and optimizing a policy against it is one approach to aligning AI systems with individual users. From a fairness perspective,…
BrainBench: Benchmarking Large Language Models for Comprehensive EEG Understanding
arXiv:2608.04156v2 Announce Type: replace-cross Abstract: Electroencephalography (EEG) analysis extends beyond assigning predefined labels to recordings; it requires workflows connecting natural-language instructions,…
Process Optimization Under Uncertainty for Improving the Bond Quality of Polymer Filaments in Fused Filament Fabrication
arXiv:2608.18431v1 Announce Type: cross Abstract: This paper develops a computational framework to optimize the process parameters such that the bond quality between extruded polymer filaments is maximized in fused…
Coupled-cluster molecular properties across the main group that extrapolate beyond training size
arXiv:2608.18346v1 Announce Type: cross Abstract: Coupled-cluster theory defines the accuracy standard for molecular electronic-structure properties but scales too steeply for routine application, whereas…
Bridge Graphical Models: Coupling, Projection, and Current-Preserving Dynamics for Generative Modeling
arXiv:2608.19144v1 Announce Type: new Abstract: Continuous-time generative models are often built from endpoint-conditioned bridges, but generation requires a different object: a non-anticipative Markov decoder that…
Online Conformal Anomaly Detection with Prediction-Powered Data Acquisition
arXiv:2505.01783v2 Announce Type: replace Abstract: Online anomaly detection is essential in fields such as cybersecurity, healthcare, industrial monitoring, and telecommunications, where promptly identifying deviations…
Accurate Decoding of Natural Sentences from Non-Invasive Brain Recordings
arXiv:2608.18114v1 Announce Type: cross Abstract: Restoring communication for people who have lost the ability to speak or move after a brain injury is a major challenge. While intracranial implants now enable…
Demystifying Training-Time Augmentation for Data-Constrained Language Model Pretraining
arXiv:2606.16246v3 Announce Type: replace Abstract: As AI labs approach a data ceiling where compute capacity outpaces the rate of new high-quality text generation, language model pretraining is shifting toward a…
MITRE-SAGE: A Multi-Agent Cybersecurity Question-Answering Model
arXiv:2608.16921v2 Announce Type: replace-cross Abstract: Effective cybersecurity operations require timely and accurate analysis of large-scale heterogeneous security information; however, analysts increasingly…
L\'evy Attention: Single-Pass Predictive Uncertainty for Continuous-Time Attention
arXiv:2608.19171v1 Announce Type: new Abstract: Deep models for irregularly-sampled time series answer queries at arbitrary continuous timestamps, yet report nothing about how far each answer should be trusted. We show…
WorldPack: Dynamic Frame Compression for Long-context Video World Modeling
arXiv:2512.02473v3 Announce Type: replace-cross Abstract: Video world models have attracted significant attention for their ability to produce high-fidelity future visual observations conditioned on past observations…
Foundations of Diffusion Models in General State Spaces: A Self-Contained Introduction
arXiv:2512.05092v2 Announce Type: replace-cross Abstract: Although diffusion models now occupy a central place in generative modeling, introductory treatments commonly assume Euclidean data and seldom clarify their…
Think Shallow, Solve Deep: Controlling Recurrent Dynamics for Reliable Test-Time Depth
arXiv:2608.18222v1 Announce Type: new Abstract: Recurrent-depth reasoners aim to solve harder problems by iterating their update longer at test time, but additional iterations can improve, preserve, or degrade an…
You Are What You Prompt: Prompt Quality, Domain Shift, and Uncertainty in Agrifood Vision-Language Models
arXiv:2608.18116v1 Announce Type: cross Abstract: Vision-language models enable zero-shot classification through natural language prompts, but performance is sensitive to prompt formulation, especially in specialized…
Grouping the Stochastic Machine: Precision, Not Capability, as the Frontier Metric for AI Systems
arXiv:2608.19140v1 Announce Type: cross Abstract: Frontier language models are compared, marketed, and benchmarked on capability -- what their best or average output can achieve. I argue this measures the wrong axis.…
Fuzzy Accuracy Compensates for Label Subjectivity in Classification of Skin Tone Using Wearable Photoplethysmography Signals
arXiv:2608.18969v1 Announce Type: new Abstract: We consider the problem of classification of skin tone using photoplethysmography (PPG) signals with labels of the ordinal six-class Fitzpatrick skin tones. A typical…
Classifying Directional Trajectories Near Criticality in the Three-State Majority-Vote Model with Deep Belief Networks and Bidirectional GRUs
arXiv:2608.18235v1 Announce Type: new Abstract: In this work, we investigate whether the latent representations learned by a Deep Belief Network (DBN) and a Bidirectional Gated Recurrent Unit (Bi-GRU) can discriminate…
Gated Graph Attention Networks with Learnable Temperature
arXiv:2605.29803v2 Announce Type: replace Abstract: Graph attention networks learn neighbor importance through data-dependent coefficients, but standard layers lack explicit control over unreliable feature dimensions…
TokenPowerSandbox: Evidence-Gated CPU-First Screening for Energy-Aware LLM Serving
arXiv:2608.18149v1 Announce Type: cross Abstract: Energy-aware LLM serving requires comparing configurations under realistic request shapes, yet exhaustive target-GPU profiling is costly and a cheap predictor can be…
What is Missing from AI Post-Training AI: An Empirical Analysis
arXiv:2608.19072v1 Announce Type: cross Abstract: Large language model (LLM) agents can now post-train an LLM end-to-end. They can write code, launch training, evaluate checkpoints, and improve downstream performance,…
Prototype-based Self-Supervised Multimodal Learning for PPG and Accelerometry Signals
arXiv:2510.09764v3 Announce Type: replace Abstract: Modeling multi-modal time-series data is critical for capturing system-level dynamics, particularly in biosignals where modalities such as ECG, PPG, EDA, and…
Model Card for OpenAI Privacy Filter
arXiv:2608.18274v1 Announce Type: cross Abstract: OpenAI Privacy Filter is a compact, bidirectional token-classification model for detecting and redacting personally identifiable information (PII) and secrets in…
rl-triton: High-Performance Triton GPU Kernels for Reinforcement Learning Credit Assignment
arXiv:2608.17641v2 Announce Type: replace Abstract: We present rl-triton, an open-source library of high-performance GPU kernels for reinforcement learning credit assignment, implemented in Triton. The core contribution…
Quantum-Logic Tsetlin Machines: Interpretable Quantum Machine Learning with Commuting Projector Clauses
arXiv:2608.18659v1 Announce Type: cross Abstract: Tsetlin Machines (TMs) learn interpretable Boolean clauses using finite-state automata. We introduce the Quantum-Logic Tsetlin Machine (QL-TM), which replaces Boolean…
Jacobian-Guided Anisotropic Noise Reshaping for Enhancing Representation Utility under Local Differential Privacy
arXiv:2605.16812v3 Announce Type: replace Abstract: While Local Differential Privacy (LDP) serves as a foundational primitive for distributed data collection, its stringent randomization requirements often lead to…
FraudBench: Stress-Testing Policy-Grounded Banking Agents Against Adaptive Fraud
arXiv:2608.18136v1 Announce Type: cross Abstract: Conversational agents now act for end users through tools while holding access to customer databases and internal policy documents that a caller can reach through…
Evaluating Structured Information Extraction with Open Models in a High Risk Public Sector Application
arXiv:2608.18289v1 Announce Type: cross Abstract: The extraction of structured information from unstructured documents represents a critical component of digital transformations in all sectors. While proprietary…
Evaluating and Explaining Prompt Sensitivity of LLMs Using Interactions
arXiv:2608.18539v1 Announce Type: new Abstract: The remarkable capabilities of large language models (LLMs) are often undermined by their instability. Even subtle and semantically irrelevant changes in prompts can cause…
Co-RL: Unsupervised Reasoning Emerges from Diverse Cohort in Multi-agent RL
arXiv:2608.17253v2 Announce Type: replace Abstract: Reinforcement learning (RL) has emerged as a powerful approach for improving reasoning in language and vision-language models, yet its strongest successes still depend…
Pairwise Ranking Outperforms Single-Action RL for Offline Explanation Selection: A Practical Lesson
arXiv:2608.18531v1 Announce Type: cross Abstract: Industrial explainable-recommendation systems built on LLMs incur a substantial serving cost: each request triggers an LLM generation, with latency in the hundreds of…
MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
arXiv:2605.03103v2 Announce Type: replace-cross Abstract: Semi-structured information extraction (IE) from OCR-derived clinical reports is crucial for efficiently reconstructing patients' longitudinal medical histories.…
Breaking the weakest link to evade vision language models
arXiv:2608.18938v1 Announce Type: cross Abstract: Vision Language Models (VLMs) have recently emerged as a critical component of multimodal AI systems, enabling joint reasoning over visual and textual inputs in…
Mitigating Spectral Bias in Neural Operators for Underwater Transmission Loss Prediction
arXiv:2608.18141v1 Announce Type: cross Abstract: Predicting underwater acoustic transmission loss rapidly and accurately is crucial for real-time ocean acoustic applications. While Fourier Neural Operators (FNO) have…
Learning Random Geometric Graphs Drawn in Probabilistic Metric Spaces
arXiv:2608.19082v1 Announce Type: cross Abstract: We present a new data-driven learning of a Random Geometric Graph (RGG) of a multivariate dataset, where the graph is drawn in a probabilistic metric space. This graph…
Self-supervised In-context Operator Learning for Stochastic Mean-Field Control
arXiv:2608.18282v1 Announce Type: cross Abstract: Stochastic mean-field control (MFC) provides a fundamental framework for coordinating large populations of interacting agents under uncertainty, with a wide range of…
Multi-stage neural operator learning with application for convolutions
arXiv:2608.18851v1 Announce Type: new Abstract: Convolution integrals widely exist in applications, and to enable fast and accurate computations, this paper introduces two general multi-stage neural operator learning…
Transforming Heart Disease Prediction with Advanced Machine Learning Techniques
arXiv:2608.18687v1 Announce Type: new Abstract: Heart disease remains the leading cause of mortality globally, necessitating early and accurate detection to improve patient outcomes. This research focuses on the…
Accelerating Visual On-Policy Distillation with Batched Speculative Jacobi Rollouts
arXiv:2608.18183v1 Announce Type: new Abstract: Visual on-policy distillation (OPD) improves the training of compact visual autoregressive models by learning from trajectories generated by the current student. However,…
CausalProfiler: Generating Synthetic Benchmarks for Rigorous and Transparent Evaluation of Causal Machine Learning
arXiv:2511.22842v3 Announce Type: replace Abstract: Causal machine learning (Causal ML) aims to answer "what if" questions using machine learning algorithms, making it a promising tool for high-stakes decision-making.…
Harness Continual Learning: Continual Adaptation Beyond Model Parameters
arXiv:2608.19013v1 Announce Type: new Abstract: Continual learning has largely been model-centric, treating model parameters as the state that changes with sequential experience. Modern agents can also adapt through a…
When Does Dynamic Ensembling Pay Off? Diagnosing Regionwise Gains in Regression under Distribution Shift
arXiv:2608.18330v1 Announce Type: new Abstract: Whether input-dependent ("dynamic") combination of a regression model pool beats the best static blend depends on the shift and is rarely known before deployment. Can a…
SESSE: Sketch, Expand, Sort, Summarize, Evaluate -- LLM-as-Judge Evaluation via Structured Decomposition
arXiv:2608.18303v1 Announce Type: cross Abstract: LLM-as-judge evaluation reduces response quality assessment to a single holistic A/B preference choice, providing no mechanism to isolate which quality dimensions drove…
Escaping Local Minima Provably in Non-convex Matrix Sensing: A Deterministic Framework via Simulated Lifting
arXiv:2602.05887v3 Announce Type: replace Abstract: Low-rank matrix sensing is a fundamental yet challenging nonconvex problem whose optimization landscape typically contains numerous spurious local minima, making it…
The Label Horizon Paradox: Rethinking Supervision Targets in Financial Forecasting
arXiv:2602.03395v5 Announce Type: replace Abstract: While deep learning has revolutionized financial forecasting through sophisticated architectures, the design of the supervision signal itself is rarely scrutinized. We…
Hierarchical Classification via Cascading Feature Elimination: Application to Human Phenotype Ontology-Aligned Facial Phenotyping (FaceMesh2HPO)
arXiv:2607.05585v2 Announce Type: replace-cross Abstract: FaceMesh2HPO is a framework for classifying facial phenotypic descriptors aligned with the Human Phenotype Ontology (HPO) to support clinical diagnosis. Using…
Converting Expert Deliberation into Financial Signals Through A Context-Aware NLP Pipeline
arXiv:2608.18911v1 Announce Type: new Abstract: We introduce the CDSP (context-conditional deliberation signal pipeline), converting an investment committee's meeting transcripts into structured predictive features.…
Computational Measurement of Team-Process Phase Dynamics in Collaborative Virtual Reality
arXiv:2608.18660v1 Announce Type: new Abstract: Collaborative virtual reality (VR) environments make team communication observable as it unfolds, but conventional transcript analyses often summarize entire trials or…
Untrainable elements determine what physical learning remembers
arXiv:2608.00097v2 Announce Type: replace-cross Abstract: Physical learning rules such as equilibrium propagation (EP), coupled learning (CL), and adjoint coupled learning (AL) train resistive networks through local…
FlashAttention for Scalable Vector Architectures
arXiv:2608.18656v1 Announce Type: new Abstract: Inference with transformer models on CPUs is increasingly important, especially for Small Language Models (SLMs), where vector architectures are emerging as a promising…
Continuous-Time Reinforcement Learning for Controlled Hawkes Jump-Diffusions
arXiv:2608.19151v1 Announce Type: new Abstract: We study stochastic control of multivariate Hawkes-driven stochastic differential equations with machine learning algorithms in a non-Markovian setting. Due to the path…
Bernstein-Vazirani Networks: Quantum Machine Learning by Interference
arXiv:2608.19043v1 Announce Type: cross Abstract: We introduce Bernstein-Vazirani Networks (BVNs), a non-variational quantum machine learning framework that leverages quantum interference for supervised learning,…
FiLoRA: Focus-and-Ignore LoRA for Controllable Feature Reliance
arXiv:2602.02060v2 Announce Type: replace Abstract: Multimodal foundation models integrate heterogeneous signals across modalities, yet it remains unclear whether their predictions can be controlled by explicitly…
Multi-Class Electrical and Mechanical Fault Classification Using Random Convolutional Kernels
arXiv:2608.18716v1 Announce Type: new Abstract: Diagnosing faults in rotating machinery is essential for ensuring the reliability of industrial processes. Random convolutional kernel-based Time Series Classification…
Automated Computational Energy Minimization of ML Algorithms using Constrained Bayesian Optimization
arXiv:2407.05788v2 Announce Type: replace Abstract: Bayesian optimization (BO) is an efficient framework for optimization of black-box objectives when function evaluations are costly and gradient information is not…
Temporal Multi-Signal Fusion for Token-Level Hallucination Detection
arXiv:2608.18115v1 Announce Type: cross Abstract: Token-level hallucination detectors score each token independently from a single signal, and fail exactly when the generating model is confidently wrong. This paper…
Assessing Quality of Experience in Natural Language Generation of German Text
arXiv:2608.18888v1 Announce Type: new Abstract: The rapid advancement of Natural Language Generation (NLG) has made the reliable evaluation of generated text increasingly critical, as these systems, such as large…
How Do Agents Fail on AutoResearch: End-to-End Diagnostic Evaluation on 100 Real-World Frontier Research Tasks
arXiv:2608.14905v2 Announce Type: replace Abstract: AI has long assisted scientific research, but the rapid advance of LLMs and agentic scaffolds is reshaping the landscape; a single system can now carry whole-stage…
Alignment Is All You Need: Instruction-Free Training for General Audio-Language Models
arXiv:2608.18132v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are typically built through a multi-stage pipeline consisting of cross-modal alignment, supervised fine-tuning (SFT), and…
Identifying Implicit Premises for Logical Reconstruction of Argument Graphs
arXiv:2608.18821v1 Announce Type: new Abstract: The logical reconstruction of argument graphs from natural language text is challenging because of the prevalence of enthymemes (i.e., arguments with implicit premises).…
Are LLMs Safe Beyond Text: Do Emojis Expose Gaps in Safety Evaluation
arXiv:2608.18164v1 Announce Type: new Abstract: Safety evaluations of large language models (LLMs) predominantly rely on text-based adversarial prompts, potentially overlooking vulnerabilities arising from alternative…
ChainWorld: Composing Long-Horizon Desktop Workloads from Atomic OSWorld Tasks
arXiv:2606.21654v2 Announce Type: replace-cross Abstract: Computer use agents are evaluated almost exclusively on atomic desktop tasks, but realistic desktop work requires sustaining state across multiple objectives. We…
When Do LLMs Actually Help? Evaluating LLMs as Data Quality Annotators
arXiv:2608.18158v1 Announce Type: new Abstract: LLMs have been increasingly used to catch data quality issues automatically, but we know very little about how consistent these judgments actually are. This study tests an…
AI Can Learn Scientific Taste
arXiv:2603.14473v3 Announce Type: replace Abstract: Scientific discovery depends on expert judgement and foresight, which we call scientific taste: the ability to judge and propose research ideas with the potential for…
Cross-Model Memory Transfer via Target-Side Reader Adaptation
arXiv:2608.17050v2 Announce Type: replace Abstract: Methods for improving knowledge use in large language models typically fall into two regimes. Non-parametric retrieval offers flexible access to external knowledge,…
EgoMemReason: A Memory-Driven Reasoning Benchmark for Long-Horizon Egocentric Video Understanding
arXiv:2605.09874v2 Announce Type: replace-cross Abstract: Next-generation visual assistants, such as smart glasses, embodied agents, and always-on life-logging systems, must reason over an entire day or more of…
Artifact-centered Claim-aware Observability for Autonomous Scientific Agents
arXiv:2608.18312v1 Announce Type: new Abstract: Autonomous scientific agents now increasingly propose ideas, write code, run experiments, analyze results, and even draft papers. Observe and audit those agents are…
Metrics That Write Themselves: Evolving an Evaluator from Its Own Blind Spots
arXiv:2608.18744v1 Announce Type: cross Abstract: Agents improve quickly against a reliable automatic metric and stall without one, and the applications that need them most, report generation among them, are the ones…
Efficient Adaptation of LLMs for Hate Speech Detection in Low-Resource Languages: A Comparative Study on Roman Urdu
arXiv:2608.18142v1 Announce Type: cross Abstract: It is challenging to detect hate speech in Low Resource Languages (LRLs) because of the absence of annotated data, the informality of its language structure, and the…
Reconstruction: A Blind Benchmark for Recovering Research Ideas from Pre-Publication Bibliographies
arXiv:2608.16645v2 Announce Type: replace-cross Abstract: Can a language model recover the true research idea of a published paper when given only that paper's pre-publication bibliography? We introduce Reconstruction,…
Building real-time digital twin instances with Function+Data Flow: user evaluation and extension for iterative pipelines
arXiv:2608.18480v1 Announce Type: cross Abstract: Digital twins (DTs) increasingly leverage artificial intelligence (AI) and machine learning (ML) pipelines, both to build real-time DTs from high-fidelity simulations…
Abliteration Mitigation via Refusal Aliases
arXiv:2608.18093v1 Announce Type: new Abstract: Abliteration, the removal of refusal capabilities from large language models by projecting weight matrices orthogonal to an extracted refusal direction, has emerged as a…
Key Coverage Matters: Semi-Structured Extraction of OCR Clinical Reports
arXiv:2605.09440v2 Announce Type: replace Abstract: Clinical reports are often fragmented across healthcare institutions because privacy regulations and data silos limit direct information sharing. When patients seek…
Computational Orientalism: Measuring Structural Discourse Bias in Large Language Models Using the Middle East Cultural Sensitivity Score (MECSS)
arXiv:2608.18100v1 Announce Type: new Abstract: AI systems now shape how hundreds of millions of people learn about cultures other than their own. When someone asks one of these systems about the Middle East, they do…
Future Policy Approximation for Offline Reinforcement Learning in LLM Reasoning
arXiv:2509.19893v3 Announce Type: replace Abstract: Reinforcement learning (RL) has emerged as a key driver of post-training for complex reasoning in large language models (LLMs), yet online RL introduces substantial…
DeepWeaver: Bridging the Evidence Synthesis Gap in Open-Ended Question Answering
arXiv:2608.18988v1 Announce Type: new Abstract: Retrieve-then-generate pipelines are commonly used to produce deep-research answers for open-ended questions, but retrieval alone is insufficient: LLMs must organize noisy…
Tangut Word Segmentation under Extreme Resource Scarcity: Integrating Traditional Lexicons and Unlabeled Text
arXiv:2608.18437v1 Announce Type: new Abstract: Tangut is an extinct language whose script does not explicitly mark word boundaries. We present the first systematic study of Tangut word segmentation using 2,750…
OmniAlign: A Unified Multilingual Aligner for Word and Sentence Alignment
arXiv:2608.18474v1 Announce Type: new Abstract: Cross-lingual sequence alignment is fundamental for building and exploiting parallel corpora, spanning mappings from documents and sentences down to words and subwords.…
Multimodal Rapport Estimation in Real-World HRI
arXiv:2608.18401v1 Announce Type: cross Abstract: Evaluating interaction quality in real-world HRI is an important challenge. If interaction quality can be estimated reliably, the results can be used to improve dialogue…
Comment-level Topic Drift Analysis in the Reddit Corpus
arXiv:2608.19133v1 Announce Type: new Abstract: We present a novel application of embedding-based dynamic topic modeling techniques to detect and quantify topic drift at the comment level in a massive corpus. By…
Repeatability is not recovery: Quantifying algorithmic stability and topic recovery in Latent Dirichlet Allocation
arXiv:2511.12850v2 Announce Type: replace Abstract: Topic models are often judged by the consistency of their outputs across repeated runs, implicitly assuming that repeatable topic output is a successful recovery of…
Persona-Guided LLM Agents for Task-Oriented Dialogue
arXiv:2608.18085v1 Announce Type: new Abstract: Prior work has shown that large language models (LLMs) can express diverse personality traits in open-ended text generation. However, it remains unclear whether they can…
Can a Lightweight Multimodal Model Estimate LLM Reasoning Performance? A Study for Compute-Optimal Document Inference
arXiv:2608.18591v1 Announce Type: cross Abstract: Uniformly allocating inference reasoning budgets to LLMs is expensive and prone to over-thinking penalties; especially in document tasks where visual layouts drive…
Nine Emotion Centroids: A Label-Free Valence Axis That Transfers Across Four Modalities
arXiv:2608.18090v1 Announce Type: new Abstract: Inside a modern language model sits a single internal direction that tracks how positive or negative a sentence feels. We show how to find this valence axis (V-axis) from…
Same Facts, Different Updates: Inference Setup Shapes LLM Behavior in Medical Allocation
arXiv:2608.18108v1 Announce Type: new Abstract: Large language models are being incorporated into sensitive and important decision-making processes across nearly all fields. While prior work studies model bias around…
Learning What to Fail On: Failure-Mode Contextual Bandits for Adversarial Data Curation
arXiv:2608.18681v1 Announce Type: new Abstract: We introduce a failure-aware adversarial retrieval-augmented framework for improving robustness in natural language understanding. Rather than selecting synthetic examples…
Adaptive Memory and Reflection Multi-Agent System for Medical Question Answering
arXiv:2608.19029v1 Announce Type: cross Abstract: Accurate and responsible medical question answering (QA) is important in healthcare, where complex cases require factual knowledge and nuanced reasoning. Existing…
Train the Model, Not the Reader: Decodability Supervision for Verifiable Activation Explanations
arXiv:2607.20379v2 Announce Type: replace-cross Abstract: Natural-language autoencoders score explanations of hidden activations by reconstruction. An explanation is deemed faithful if the activation can be regenerated…
Backdoor Learning in Language Models and Vision-Language Models
arXiv:2608.18095v1 Announce Type: new Abstract: Recent advances in deep learning have significantly enhanced the capabilities of Natural Language Processing (NLP) and Vision-Language Models (VLMs). However, these…
When Readability and Source Retention Diverge: An Evaluability Gap in AI Translation
arXiv:2608.19083v1 Announce Type: cross Abstract: Readable AI output can leave an evaluability gap: even when the source is shown, an overall-quality judgment may not reflect what an output preserves. We investigated…
From Sequence to Structure: Relational Uncertainty Propagation for LLM Agents
arXiv:2608.16002v2 Announce Type: replace Abstract: Reliable uncertainty quantification (UQ) is essential for deploying large language model (LLM) agents in complex interactive environments. Existing UQ methods largely…
Operationalizing Narrative Entropy (Sn): A Two-Scene Registered Pilot Report and Pre-Validation Protocol
arXiv:2608.18109v1 Announce Type: new Abstract: Narrative Entropy ($S_n$) is a proposed quantitative descriptor within the Bulut Doctrine, intended to capture the rate at which a narrative text imposes processing load…
Self-Improvement of Large Language Models: A Technical Overview and Future Outlook
arXiv:2603.25681v2 Announce Type: replace Abstract: As large language models (LLMs) continue to advance, improving them solely through human supervision is becoming increasingly costly and limited in scalability. As…
ComponentBench: Diagnosing Component-Level Failures in Computer-Use Agents
arXiv:2608.18307v1 Announce Type: cross Abstract: Current evaluation of computer-use agents is split between long-horizon workflow benchmarks and atomic GUI-grounding tests. This leaves an under-instrumented middle…
LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum
arXiv:2601.01684v2 Announce Type: replace-cross Abstract: While dense retrieval models have been the standard for state-of-the-art information retrieval, their deployment is often constrained by high memory requirements…
Efficient INT8 Inference of Small NLP Models on Server CPUs with PyTorch Native Stack
arXiv:2608.18182v1 Announce Type: new Abstract: Small NLP models, especially BERT-family encoders, remain important in industrial workloads such as classification, ranking, and retrieval even in the era of large…
rEDMRec: Distilling Large Language Model Reasoning into an Editable Experience Memory for Recommendation
arXiv:2608.18952v1 Announce Type: cross Abstract: Large language models can improve recommendation quality by reasoning explicitly over user history and candidate items - for example, extracting a user's preferences or…
The Deontic Gap: Large Language Models and the Modal Language of Obligation
arXiv:2608.18144v1 Announce Type: new Abstract: Modal auxiliaries such as must, should, and have to mark necessity and obligation within the contexts of speaker authority and interpersonal stance. We examine whether…
When to Call an Apple Red: Humans Follow Introspective Rules, VLMs Don't
arXiv:2604.06422v2 Announce Type: replace Abstract: Understanding when Vision-Language Models (VLMs) will behave unexpectedly, whether models can reliably predict their own behavior, and if models adhere to their…
MissDiag: Diagnostic Evaluation of Incomplete-Knowledge Robustness in KGQA and KG-RAG
arXiv:2608.18489v1 Announce Type: new Abstract: Knowledge graph question answering (KGQA) and knowledge-graph-based retrieval-augmented generation (KG-RAG) aim to ground answers in explicit graph evidence, but…
KA2L: A Knowledge-Aware Active Learning Framework for LLMs
arXiv:2603.17566v2 Announce Type: replace Abstract: Fine-tuning large language models (LLMs) with high-quality knowledge has been shown to enhance their performance effectively. However, there is a paucity of research…
Readable, Faithful, Used: Three Dissociable Properties of Demographic Identity in a Language Model
arXiv:2608.18768v1 Announce Type: new Abstract: Large language models are widely used to simulate survey respondents, yet their answers are homogeneous and unfaithful to real inter-group differences. We ask where…
TranslatePsy-AfriSLM: High-Quality Data Scaling For Low-Resource Machine Translation
arXiv:2608.18655v1 Announce Type: new Abstract: The rapid progress in Artificial Intelligence has largely bypassed African languages, creating a digital divide that limits AI adoption on the continent. Recent…
Different Facets of Verbalised Overconfidence: an Interpretability Study
arXiv:2608.18106v1 Announce Type: new Abstract: Large language models tend to overconfidence, giving assertive answers when the evidence suggests hedging or abstention. Using controlled reasoning scenarios that…
MicroPython and CircuitPython: Pythons Quiet Takeover of IoT and Robotics
arXiv:2608.18160v1 Announce Type: cross Abstract: Background: Python has become the dominant language in software and data science, yet embedded systems have remained tied to C/C++ due to performance and memory…
Test-Time Scaling in the Wild: Why Exploitation, Not Exploration, Is the Bottleneck
arXiv:2608.18931v1 Announce Type: new Abstract: Test-time scaling (TTS) improves language model outputs by spending additional inference compute - generating multiple candidates, searching over partial sequences, or…
LongNovel: A Multi-Scale Benchmark for Hallucination Detection in Long-Context Novel Summarization
arXiv:2608.18082v1 Announce Type: new Abstract: Although context windows have expanded significantly in recent years, hallucinations in long-context summarization remain a challenge. Long novels are better suited than…
GreekBarRetrieval: A Benchmark for Greek Statutory Retrieval
arXiv:2608.18752v1 Announce Type: cross Abstract: Statutory retrieval is necessary for citation-grounded legal question answering, but remains underexplored for Greek. We introduce GreekBarRetrieval, a public retrieval…
ReWEIGH the Evidence: Calibrating Token-Level Ordinal Visual Evidence to Mitigate Hallucinations in Large Vision-Language Models
arXiv:2608.19075v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) often hallucinate, generating content that the input image does not support. Preventing such content during decoding calls for a…
MMD-Flagger: Leveraging Maximum Mean Discrepancy to Detect Hallucinations
arXiv:2506.01367v4 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly integrated into agentic AI systems, yet their propensity to generate hallucinations remains a critical safety concern.…
Compiler-Guided Adaptive Proof Search with Cross-Model Synergy on Context-Dependent Theorem Proving
arXiv:2608.18084v1 Announce Type: new Abstract: Theorem proving in real-world Lean 4 projects is challenging because proofs often depend on project-specific context. While iterative refinement can use compiler errors to…
Entity tracking emerges in sub-billion parameter language models and exceeds human performance in naturalistic narratives
arXiv:2608.18083v1 Announce Type: new Abstract: Understanding language requires tracking entities across discourse - i.e., knowing where things are and how they change, even when not explicitly stated. Whether language…
Latent Space Refusal Anchoring for Low-Resource African Languages: Mechanistic Safety Recovery Without Retraining
arXiv:2608.18089v1 Announce Type: new Abstract: Instruction-tuned models often refuse harmful requests in English but comply with the same requests in Yoruba, Igbo, Igala, and Hausa. This suggests that the refusal…
NE-BERT: A Multilingual Language Model for Nine Northeast Indian Languages
arXiv:2608.18094v1 Announce Type: new Abstract: Large pretrained language models have demonstrated remarkable capabilities across diverse languages, yet critically underrepresented low-resource languages remain…
Execution-grounded evaluation reveals hidden failures in language-model calculations for environmental science
arXiv:2608.18726v1 Announce Type: new Abstract: Large language models are increasingly used for quantitative work in the environmental sciences, yet existing evaluations score only final answers, leaving calculation…
Introducing the Privacy-HSD Trade-off: Hate Speech Detection, but not at the Cost of Privacy
arXiv:2608.19006v1 Announce Type: new Abstract: Hate speech is a real and timely threat that affects a large portion of online users, especially youth and minority groups. While building reliable and robust automatic…
Institutional Newspapers Pipeline: Deriving billions of high quality tokens from historical newspapers
arXiv:2608.18972v1 Announce Type: new Abstract: Historical newspapers are an abundant record of public life, but their dense, irregular and sometimes noisy layouts make computational access to these materials both…
SMTrap: Cost-Effective DoS Attacks Against Large Reasoning Models via SMT Conflict Guidance
arXiv:2608.18921v1 Announce Type: new Abstract: Existing LRM-DoS methods rely heavily on model feedback to synthesize attack queries, requiring either repeated queries to the target model or training a dedicated attack…
X2-Turn: Frame-Synchronous Dual-Head Modeling for Joint Streaming ASR and Turn State Prediction
arXiv:2608.10878v2 Announce Type: replace Abstract: Accurate and responsive turn-taking is essential for spoken dialogue systems, which must distinguish in real time between user interruptions, backchannels that should…
Decomposing Wrong-Consensus Agreement in LLM Self-Consistency: A GPT-4.1 Case Study
arXiv:2608.18795v1 Announce Type: new Abstract: Majority voting over multiple LLM samples is widely used to raise answer accuracy, yet its gain varies erratically: on hard questions it can even backfire. This paper…
Neurosymbolic Embodied Agents
arXiv:2608.16794v2 Announce Type: replace-cross Abstract: Language and vision-language models generate plausible embodied plans but do not guarantee executability, as their outputs can violate environment dynamics or…
Predicting the Benefit of Retrieval Augmentation in Open-Domain Question Answering
arXiv:2604.07985v3 Announce Type: replace Abstract: While retrieval augmented generation has become a common approach for enhancing question answering systems, retrieval is not universally advantageous. We study the…
Trace, Verify, and Correct: A Training-Free Framework for Spatial Reasoning in Multimodal LLMs
arXiv:2608.04759v2 Announce Type: replace-cross Abstract: Although Multimodal Large Language Models (MLLMs) have made substantial progress, their spatial reasoning may still produce intermediate judgments inconsistent…
ChildSafeAds Shared Task 2026: Commercial Content in Child-Facing YouTube Videos
arXiv:2608.19165v1 Announce Type: new Abstract: ChildSafeAds is a shared task on commercial content in YouTube videos likely to reach children and teenagers. It contains 3,360 videos from 939 channels. Each instance…
Do Large Language Models Hallucinate Electric Fata Morganas?
arXiv:2608.18816v1 Announce Type: new Abstract: AI hallucinations - that is, outputs which are made up, cannot be verified, or contradict the source material - are generally regarded as an engineering flaw to be dealt…
SeqFeed: Improving Agentic RTL Code Generation with Sequential Behavior Feedback
arXiv:2608.16934v2 Announce Type: replace-cross Abstract: RTL code generation is a critical stage in hardware design, and the emergence of agentic systems offers new opportunities to automate this process. To generate…
FrenchNews-7: Benchmarking Cross-Publisher French News Editorial Desk Classification
arXiv:2608.18097v1 Announce Type: new Abstract: We present FrenchNews-7, a cross-publisher France-based French-language news editorial desk classification benchmark combining a large multi-outlet corpus, a URL-derived…
Tatarstan Toponyms: A Bilingual Dataset and Hybrid RAG System for Geospatial Question Answering
arXiv:2605.05962v2 Announce Type: replace Abstract: This paper addresses end-to-end geospatial question answering over multilingual toponymic data. We introduce a bilingual (Russian-Tatar) dataset of 9,688 toponyms with…
Figurative and Cultural Knowledge in LLMs: Investigating Cross-Domain Transfer through Fine-Tuning
arXiv:2608.18361v1 Announce Type: new Abstract: Figurative language is deeply culturally embedded; fluent use requires not just linguistic competence but cultural immersion. We ask whether LLMs can learn this link: does…
Intercepting the Kangaroo: Experimental Astrolinguistics with Constructed Lexicons, Active Probing, and Large Language Models as Informants and Hypothesis Proposers
arXiv:2608.19124v1 Announce Type: new Abstract: Astrolinguistics -- communication with minds that categorize reality differently from ours -- has been purely speculative since Freudenthal's Lincos (1960). We make it…
Budget-First Tariff Recommendation (BFTR): A Complete Algorithmic Framework for Telecom Plan Recommendation without Overcharging
arXiv:2608.18723v1 Announce Type: new Abstract: Telecom operators traditionally offer predefined tariff grids, forcing users to choose from a limited set of plans. This paper proposes BFTR (Budget-First Tariff…
SuTRA : Structurally-Unified Tokenization with Root Awareness
arXiv:2608.18087v1 Announce Type: new Abstract: Existing subword tokenizers optimize statistical compression but ignore morphological structure, particularly the relationship between roots and affixes. This is harmful…
Shared Circuits for Shared Grammar: Tracing Subject-Verb Agreement Across Languages
arXiv:2608.18545v1 Announce Type: new Abstract: Multilingual large language models often generalize across languages, and prior work suggests that their internal mechanisms can overlap cross-lingually. It remains…
Institutional Books - Enriched Text: A customizable multilingual open-source pipeline for denoising, deduplicating, and annotating OCR text at scale
arXiv:2608.19026v1 Announce Type: new Abstract: Released in 2025, Institutional Books: Harvard Library (IB-HL) is a collection of 983,004 volumes (242B o200k_base tokens), originally digitized through Harvard Library's…
Fractional Decay KV-Cache: Ownership-Aware Memory Management for Improved Inference Relevancy in Dialog Systems
arXiv:2608.18098v1 Announce Type: new Abstract: Key-value (KV) caching is essential for efficient autoregressive inference in transformer based dialog systems, yet existing strategies treat all cached entries uniformly…
An Information-theoretic Propagation Denoising and Fusion Framework for Fake News Detection
arXiv:2605.02259v2 Announce Type: replace Abstract: Incomplete propagation data significantly hinders robust fake news detection. Recent approaches leverage large language models to simulate missing user interactions…
Listening or Reading? Evaluating Speech Awareness in Chain-of-Thought Speech-to-Text Translation
arXiv:2510.03115v2 Announce Type: replace Abstract: Speech-to-Text Translation (S2TT) systems built from Automatic Speech Recognition (ASR) and Text-to-Text Translation (T2TT) modules face two major limitations: error…
EgoCITE: Context-Augmented Indexing and Time-Aware Retrieval for Long-Horizon Egocentric Memory
arXiv:2608.12627v3 Announce Type: replace-cross Abstract: Long-horizon egocentric memory transforms continuous first-person video and audio into a searchable record of past experiences. We demonstrate two bottlenecks in…
First-Token Broadcasters: Mechanistic Origins of Language Identity and Distributed Robustness in Transformers
arXiv:2606.22361v2 Announce Type: replace Abstract: Why do multilingual language models sometimes generate in the wrong language, and why is this so hard to fix? We introduce Language Identity Head Ablation (LIHA), a…
Corrections of Zipf's and Heaps' Laws Derived from Hapax Rate Models
arXiv:2307.12896v5 Announce Type: replace Abstract: The article introduces corrections to Zipf's and Heaps' laws based on systematic models of the proportion of hapaxes, i.e., words that occur once. The derivation rests…
More Context, Same Budget: Dual-Bounded Relational Recall Beyond Top-K Retrieval
arXiv:2608.18448v1 Announce Type: cross Abstract: More context does not require a larger retrieval budget. Under the same ceiling, a retrieval system can recover more of the evidence a question requires by following…
SPADE: Self-Play in Adaptive Synthetic Executable Environments
arXiv:2608.19197v1 Announce Type: new Abstract: Continuous self-improvement requires an ever-expanding pool of self-generated, diverse, adaptive goals. For language agents, existing training environment pools…
ConspirED: A Dataset for Cognitive Traits of Conspiracy Theories and Large Language Model Safety
arXiv:2508.20468v2 Announce Type: replace Abstract: Conspiracy theories erode public trust in science and institutions while resisting debunking by evolving and absorbing counter-evidence. As AI-generated misinformation…
Making Implicit Premises Explicit in Logical Understanding of Enthymemes
arXiv:2603.06114v3 Announce Type: replace Abstract: Real-world arguments in text and dialogues are normally enthymemes (i.e. some of their premises and/or claims are implicit). Natural language processing (NLP) methods…
When Audio-Language Models Fail to Leverage Multimodal Context for Dysarthric Speech Recognition
arXiv:2605.02782v2 Announce Type: replace-cross Abstract: Automatic speech recognition (ASR) systems remain brittle on dysarthric and other atypical speech. Recent audio-language models raise the possibility of…
Structure, Association, and Decision Value: Representation-Based Difficulty Estimation for Adaptive Inference in African-Language NLI
arXiv:2608.19003v1 Announce Type: new Abstract: We ask whether internal representation statistics can provide useful example-level difficulty signals for adaptive inference in multilingual African NLP, and find that…
Aslema at NADI 2026: Augmentation through Fewshot for SLU
arXiv:2608.18689v1 Announce Type: new Abstract: We present Aslema, our system for NADI 2026 Shared Task 5, which consists of two subtasks: intent recognition and slot filling. We evaluate four omni LLMs in a zero-shot…
Grading the Graders: Verification Autonomy Levels (L0-L5) for LLM Reasoning
arXiv:2608.19009v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly paired with verifiers (step checkers, self-consistency filters, tool-based fact checkers, formal proof assistants) that claim…
CanLegalRAGBench: Evaluating Retrieval-Augmented Generation on Canadian Case Law
arXiv:2605.30497v2 Announce Type: replace Abstract: RAG-based legal assistants have been growing in popularity, but LLM hallucinations remain a key issue and potentially undermines justice. While benchmarks have been…
Phantom Transitions in Language Model Fine-Tuning: A Density-Matrix Analysis
arXiv:2606.07559v3 Announce Type: replace Abstract: Language models fine-tuned where the correct completion must outrank a near-synonym competitor often fail silently. The cross-entropy loss falls monotonically while…
Dual-Stream Cross-Anchor Correction Grounding Long-Form Captions and the Domain Limits of Object-Level Anchors
arXiv:2608.12746v3 Announce Type: replace-cross Abstract: Object hallucination in multimodal large language models arises when language priors and corpus co-occurrence bias outweigh the visual evidence, with nothing…
Language Models for Portuguese: A Systematic Mapping Study
arXiv:2608.18138v1 Announce Type: new Abstract: In recent years, the rapid development of language models has transformed the field of Natural Language Processing through a wide range of applications. However, the…
SLAI T-Rex: Full-Parameter Post-training of the DeepSeek-V4 Family on Ascend SuperPOD
arXiv:2607.20145v3 Announce Type: replace Abstract: Full-parameter post-training of trillion-parameter-scale MoE models introduces substantial system-level challenges for large-scale distributed training, including…
X2Streaming-TTS: Causal Token-Level Text-to-Speech from Streaming Text with Speech-State Inheritance
arXiv:2608.18661v1 Announce Type: new Abstract: Streaming text-to-speech is essential for low-latency spoken dialogue systems, yet many systems wait for sentence-level text and are therefore only pseudo-streaming. True…
ConstructCIE: A Dataset for Extracting Causal Information from Construction Accident Narratives
arXiv:2608.06495v2 Announce Type: replace Abstract: Construction accident narratives contain rich causal information, but the evidence is often implicit, long-span, and distributed. We introduce ConstructCIE, a manually…
When Safety Overrides Vision: Exploring Dynamics between Vision Influence and Safety Alignment in Vision-Language Models
arXiv:2608.18628v1 Announce Type: cross Abstract: Aligned vision-language models (VLMs) are designed to balance grounded visual reasoning with safe generation behavior. However, we observe a striking phenomenon: under…
DeepTCM1.0: A Multi-Expert AI Agent for Deciphering Mechanisms of Chinese Herbal Formulae Based on General Large Language Models
arXiv:2608.18103v1 Announce Type: new Abstract: Background: Mechanistic elucidation of traditional Chinese medicine (TCM) compound formulas remains a central challenge in the modernization of TCM. Conventional…
MedUAG: Unified Understanding and Generation for Medical Multimodal Models
arXiv:2608.18937v1 Announce Type: new Abstract: Recent Multimodal Large Language Models (MLLMs) are rapidly evolving into unified understanding and generation (UAG) frameworks. However, extending these unified paradigms…
Beyond LLM-Based Reasoning: Lightweight GNNs for Agent Failure Attribution
arXiv:2608.18575v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems (MAS) often exhibit complex failure modes, which frequently cause agents to produce incorrect outcomes. This motivates…
Self- and Other-Labels Induce Bidirectional Bias in LLM Judges
arXiv:2608.18091v1 Announce Type: new Abstract: As LLM-as-a-judge systems become increasingly widespread, self-preference in LLMs -- the tendency to favor one's own outputs -- raises growing concerns about evaluation…
MemFuse: Multi-Source Memory Fusion from Fragmented Observations
arXiv:2608.18704v1 Announce Type: new Abstract: Long-term memory is essential for agents that operate across extended interactions, yet existing memory systems and benchmarks predominantly focus on single-source textual…
Safety Alignment Illusion: The Cross-Lingual Safety Gap in LLMs
arXiv:2608.18131v1 Announce Type: cross Abstract: Current safety alignment training for Large Language Models (LLMs) are heavily English-centric. When such safety filters fail for non-English languages, the consequences…
Institutional Prestige as Geographic Bias in Large Language Models: Evidence from Three Factorial Experiments with Bootstrap Confidence Intervals
arXiv:2608.18107v1 Announce Type: new Abstract: We investigate whether large language models (LLMs) systematically discriminate in candidate evaluations based on applicant name ethnicity and/or institutional prestige…
Position: AI Leaderboards Are Underserving the Global South: A Case Study from India
arXiv:2608.18117v1 Announce Type: new Abstract: This position paper argues that AI leaderboards are structurally ill-suited to serving the Global South because they lack independent governance, conflict-of-interest…
Global Index on Responsible AI 2026 : Conceptual Framework and Methodology
arXiv:2608.18122v1 Announce Type: cross Abstract: This report presents the methodology of the Global Index on Responsible AI (GIRAI), 2nd Edition. This edition refines the 1st Edition by strengthening the distinction…
\textsc{TestifAI}: Tomography-Based Testing for Deep Learning Systems
arXiv:2608.18900v1 Announce Type: new Abstract: As AI systems are increasingly deployed in safety-critical application domains (e.g., autonomous driving), associated risks increase too. Deep learning models underlying…
Pre-Compiled Pipeline Shards for Distributed LLM Inference on Intel AI PC Fleets
arXiv:2608.19147v1 Announce Type: cross Abstract: Modern Intel AI PCs ship capable integrated GPUs and NPUs with 16+ GB of unified memory, and they spend considerable time idle. That is not enough memory to fit a large…
CTIFoundry: An Agent-Native Corpus Scaffold for Cyber Threat Intelligence
arXiv:2608.18613v1 Announce Type: new Abstract: Cyber threat intelligence (CTI) is increasingly consumed not by human analysts but by LLM agents that compose multi-step investigations at query time. The harness side of…
Breaking Planner Integrity Boundary: Enviroment State-Text Injection Attack on LLM-Driven Embodied Agents
arXiv:2608.16806v2 Announce Type: replace-cross Abstract: Large language model (LLM)-driven embodied agents rely on environment states to interpret scenes, generate high-level plans, and drive physical execution, making…
Composed Historical Image Retrieval by Modeling Temporal Representations
arXiv:2608.18694v1 Announce Type: cross Abstract: While time evolves linearly, the geometry of neural embedding spaces is inherently multi-dimensional, often chaotic, and difficult to interpret. In principle, one could…
Competence, Not Accuracy: A Diagnostic for Reference-Free Judge Gates in Skill Optimization
arXiv:2608.18719v1 Announce Type: new Abstract: Text-space skill optimization adapts a frozen agent by evolving a natural-language skill document, accepting each candidate through a validation gate. Existing gates rely…
Wildfire Suppression: Complexity, Models, and Instances
arXiv:2603.29865v2 Announce Type: replace-cross Abstract: Wildfires cause major losses worldwide, and the frequency of fire-weather conditions is likely to increase in many regions. We study the allocation of…
Emergence of Agentic AI: A Review on Evolution, Background, Working Principles, Applications, Adoption Factors, and Future Research Directions
arXiv:2608.18110v1 Announce Type: new Abstract: Agentic AI is gaining new insights and advancements in the field of Artificial Intelligence, fostering significant potential to enable rapid transformation across various…
Impact of Iterative Fine-Tuning on Transcription Accuracy in Complex Historical Sanskrit Manuscripts
arXiv:2608.18696v1 Announce Type: cross Abstract: Digitizing the text from handwritten historical manuscripts is required to make them easily accessible, preservable, and to enable historical scholars to study them in…
A Multi-Agent Platform for Automated Enterprise Analytics and Insight Generation
arXiv:2608.18740v1 Announce Type: new Abstract: This paper proposes a multi-agent framework built on CrewAI [1] for conversational business intelligence. Five specialized AI agents operate in a sequential pipeline to…
Sensory Restoration via Brain-Computer Interfaces: A Scoping Review
arXiv:2606.15091v3 Announce Type: replace-cross Abstract: Brain-computer interfaces (BCIs) can restore sensory and motor function in individuals with severe neurological impairment, but the literature is fragmented…
Measuring the Partial-Credit Gap: A Strict Benchmark on Vietnam's 2025 Convex Marking Scheme
arXiv:2608.18336v1 Announce Type: new Abstract: When evaluating language models on human exams, benchmarks typically score each response as right or wrong and report the overall accuracy. This approach assumes that…
Learning-State-Aware Dynamic Generative Data Augmentation on Small-Scale Datasets
arXiv:2608.18907v1 Announce Type: cross Abstract: Small-scale image classification is often limited by the scarcity of training data. Generative data augmentation (GDA) based on pretrained generative models has emerged…
Detecting Backdoors in Object Detection via Pre-NMS Prediction Distribution Shift
arXiv:2608.19088v1 Announce Type: cross Abstract: Object detection models deployed in safety-critical applications remain vulnerable to backdoor attacks that cause targeted misbehaviors when a hidden trigger is present.…
Candidate-Fate Accounting for Transparent Sensor Diagnostic Pipeline Search
arXiv:2608.18665v1 Announce Type: new Abstract: Industrial sensor diagnostics relies on preprocessing, representation, and classification pipelines, making automated pipeline search useful for reducing manual design…
Improving Natural-Language Combinatorial-Optimization Accuracy in Resource-Constrained Language Models via Formal Abstractions
arXiv:2608.18409v1 Announce Type: new Abstract: Combinatorial scheduling poses a significant challenge for language models, requiring them to identify feasible solutions within exponentially large search spaces while…
SkillGate: Training In-Policy Skill Selection in Long-Horizon Agents
arXiv:2608.18852v1 Announce Type: new Abstract: Agent frameworks increasingly package procedural knowledge as skills: instruction files an agent reads on demand, while public libraries now hold thousands of them. Which…
A Framework for Measuring Appropriate Reliance on Set-Valued AI Advice
arXiv:2606.06081v2 Announce Type: replace Abstract: Appropriate reliance on AI advice has become a central research theme in human-AI collaboration. Existing frameworks have focused exclusively on point predictions as…
FinRCA-Bench: Benchmarking Evidence Retrieval and Reasoning for Financial AI Systems
arXiv:2608.18534v1 Announce Type: new Abstract: Large language models are increasingly used to support financial operations, but their apparent reasoning performance can depend on whether they receive the right…
Complete, Scalable, and Robust Prioritized Planning for Multi-Robot Ordered Storage and Retrieval at Maximum Capacity
arXiv:2608.07734v2 Announce Type: replace-cross Abstract: Automated warehouses face a fundamental trade-off between maximizing storage density and achieving high retrieval throughput. While puzzle-based storage (PBS)…
Structure-Informed Estimation for Pilot-Limited MIMO Channels via Tensor Decomposition
arXiv:2602.04083v3 Announce Type: replace-cross Abstract: Accurate channel state information in wideband MIMO systems is constrained by pilot overhead, a challenge intensifying as bandwidths scale toward 6G. This paper…
MBABench: Evaluating LLM Agents on End-to-End Spreadsheet Tasks in Finance
arXiv:2605.22664v5 Announce Type: replace Abstract: LLM agents are increasingly expected to carry out end-to-end workflows, producing complete artifacts from high-level user instructions. To meet enterprise needs,…
Coverage-Driven RTL Assertion Generation with Formal Exploration and Neuro-Symbolic Refinement
arXiv:2608.18482v1 Announce Type: cross Abstract: Hardware functional verification relies on high-quality assertions to expose design bugs and establish confidence in Register Transfer Level (RTL) designs. Yet existing…
Eureka: Task-Conditioned Meta-Agent Orchestration for Scientific Discovery
arXiv:2608.19047v1 Announce Type: new Abstract: We present Eureka, a task-conditioned Meta-Agent architecture that compiles long-horizon tasks into dynamic obligation graphs with explicit acceptance semantics. During…
From Multi-Agent to Single-Agent: When Is Skill Distillation Beneficial?
arXiv:2604.01608v5 Announce Type: replace Abstract: Multi-agent systems (MAS) for structured data-science tasks externalize analytical control through workflows spanning stages, tools, shared state, verification, and…
FM-Bench: A Benchmark for Long-Horizon Management with Competing Agents
arXiv:2608.18423v1 Announce Type: new Abstract: Language model agents now execute bounded tasks reliably. Whether they can sustain effective decision-making over long horizons, where actions have cumulative consequences…
MR-IQA-2: Faithful Image Quality Reflection via Fine-Grained Credit Assignment
arXiv:2608.18579v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have shown strong potential for image quality assessment (IQA) by improving consistency between quality ratings and their…
Self-prompting and cross-model consensus enable reproducible data extraction from scientific literature with large language models
arXiv:2608.19025v1 Announce Type: new Abstract: Accurately extracting nuanced, contextualized data from research articles is laborious and time intensive. Here, we investigate the performance of frontier, browser-based…
ContextSniper: AntTrail's Token-Efficient Code Memory for Repository-Level Program Repair
arXiv:2607.01916v5 Announce Type: replace Abstract: Large language model agents can repair real repository issues, but they often spend large context budgets on whole-file reads, broad searches, and long terminal…
Science Done on a Machine by a Machine: AI Agents in Computational Chemistry
arXiv:2608.18508v1 Announce Type: cross Abstract: We are witnessing an explosion of agentic systems for computational chemistry simulations: from half a dozen in 2024 to a dozen in 2025, and the current number…
Position: Collusion Risks Among AI Reasoning Agents Justify Certification Requirements for Making Market Decisions
arXiv:2608.18078v1 Announce Type: new Abstract: This position paper argues that AI agents with chain-of-thought reasoning capabilities are predisposed to exhibit collusive behavior and should be required to obtain…
D$^2$ACCI: A Dual-Loop Diagnostic Protocol for Evidence-Preserving Agent Memory
arXiv:2608.17756v2 Announce Type: replace Abstract: Memory is a key capability of LLM agents. Persistent memory extends this across sessions---enabling recall, revision, and personalization. Yet its multi-stage pipeline…
FinSkillBench: Evaluating AI Agents and Domain Skills for Investment Management
arXiv:2608.18099v1 Announce Type: new Abstract: Investment management is a high-stakes domain in which agentic AI systems must do more than generate plausible text. They must retrieve point-in-time data, assemble…
Horizon-Uniform Sensitivity and Decay of Terminal Reward Perturbations in Discrete-Time Pontryagin Systems
arXiv:2606.17762v3 Announce Type: replace-cross Abstract: We study local stationary solutions of finite-horizon discrete-time Pontryagin systems near a steady extremal. Suppose that the stationarity equation for the…
A Theory of Post-hoc Debate Judgement
arXiv:2608.19002v1 Announce Type: new Abstract: Debates have recently emerged as a useful methodology for agentic AI to improve performance as well as to aid explainability and user engagement. For example,…
On the Triangle Inequality for the Jaccard Distance in Arbitrary Lattices
arXiv:2608.18194v1 Announce Type: new Abstract: This paper presents new theoretical results on generalizing the Jaccard distance for lattices and real valuations. We demonstrate that when the valuation is strictly…
`From Prompt to Perturbation': An Adaptive Framework for Voice-Based Jailbreaks on Audio LLMs
arXiv:2502.00735v4 Announce Type: replace-cross Abstract: As large language models (LLMs) are increasingly integrated into audio-based applications, growing concerns have emerged regarding their vulnerability to…
A Jagged Frontier: Evaluating Robustness of Code Agents to Semantics-Preserving Transformations
arXiv:2608.18389v1 Announce Type: new Abstract: AI code agents are increasingly deployed to resolve real software issues, yet their reliability under superficial code variations remains poorly understood. We evaluate…
Interval POMDP Shielding for Imperfect-Perception Agents
arXiv:2604.20728v2 Announce Type: replace Abstract: Autonomous systems that rely on learned perception can make unsafe decisions when sensor readings are misclassified. We study shielding for this setting: given a…
OmniHandwritingOCR: A Diagnostic Benchmark for Evaluating Multimodal LLMs in Handwritten OCR Scenarios
arXiv:2608.18586v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are increasingly used as OCR systems in document and knowledge-processing pipelines, but their ability to faithfully read real…
DentAgent: Evidence-Centric Multi-Agent Coordination for Multimodal Dental Reasoning
arXiv:2608.18878v1 Announce Type: new Abstract: Oral diseases affect billions of people worldwide, underscoring a pressing need for accurate and reliable dental assessment that integrates heterogeneous evidence from…
Adversarial Review: Structured Disagreement for Grounded Agentic Code Review
arXiv:2608.18167v1 Announce Type: new Abstract: Early multi-agent LLM systems often used role-separated teams, yet scaling agent count yields diminishing returns on repository-level coding tasks. Recent alternatives…
A Few Cases Are All You Need: An Empirical Study of Annotation-Efficient LoRA Fine-Tuning of MedSAM3
arXiv:2608.18731v1 Announce Type: cross Abstract: Medical image segmentation is essential for clinical workflows such as treatment planning and disease assessment. While specialist tools like TotalSegmentator and…
Position: Multi-Agent Systems Should Prioritize Concurrency Control
arXiv:2608.18092v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) promise scalable collaboration, yet adding agents often reduces reliability. This position paper argues that many MAS failures are…
S2-MoE: Enabling Efficient Self-Speculative Decoding for Mixture-of-Experts on Edge Devices
arXiv:2608.15018v2 Announce Type: replace Abstract: Deploying large language models (LLMs) for inference on edge devices is challenging due to severe memory and bandwidth constraints. While speculative decoding and…
ORBITER: Conflict-Aware Decision-Making for Agentic Last-Mile Delivery
arXiv:2608.18846v1 Announce Type: new Abstract: Last-mile delivery aims to handle dynamically arriving orders with couriers while modeling complex spatial and temporal correlations. Recent learning-based methods model…
Bridging Search and CRM: Productionizing AI Product Research Agents for Customer Re-Engagement
arXiv:2608.18543v1 Announce Type: new Abstract: Modern e-commerce platforms often operate search, recommendation, personalization, and CRM systems independently, limiting opportunities for proactive customer…
SkillForge: Self-Distilling Agents for Project-Specific Issue Resolution
arXiv:2608.18933v1 Announce Type: cross Abstract: Large language model (LLM) based agents have demonstrated remarkable proficiency in automated software issue resolution, yet they often struggle to resolve issues in a…
A Framework and Prototype for a Navigable Map of Datasets in Engineering Design and Systems Engineering
arXiv:2603.15722v3 Announce Type: replace-cross Abstract: The proliferation of data across the system lifecycle presents both a significant opportunity and a challenge for Engineering Design and Systems Engineering…
Professional Software Developers Don't Vibe, They Control: AI Agent Use for Coding in 2025
arXiv:2512.14012v2 Announce Type: replace-cross Abstract: The rise of AI agents is transforming how software can be built. The promise of agents is that developers might write code quicker, delegate multiple tasks to…
Large Language Models in Mental Health: A Systematic Review of Applications, Innovations, and Ethical Challenges
arXiv:2608.18080v1 Announce Type: new Abstract: We present a review on the applications of large language models (LLMs) in health, e.g., social media analysis, clinical conversational agents, therapy support tools,…
TTSD-FAR: Test-Time Self-Distillation with Fisher-Anchored Restoration for Missing-Modality Emotion Recognition in LVLMs
arXiv:2608.18386v1 Announce Type: cross Abstract: Large video-language models (LVLMs) have shown remarkable performance on multimodal tasks like multimodal emotion recognition (ER) in the wild. ER is inherently…
Training-Free Inference-Time Self-Reflection and Cost-Bounded Early Stopping for Large Language Models
arXiv:2608.18884v1 Announce Type: new Abstract: Reinforcement-learning training of reasoning LLMs (e.g., GRPO) is expensive and requires a controllable environment, committing every contribution to a full training…
Epistemic Transfer in AI-Assisted Verification: A Framework and Evaluation Protocol
arXiv:2608.08882v3 Announce Type: replace-cross Abstract: AI tools that help people judge online claims are usually evaluated while the tool is present. This paper asks a different question: after using such a tool,…
A strengthening of the MCFL-ness of $O_2$
arXiv:2608.18813v1 Announce Type: cross Abstract: In the last years, a number of proofs of the fact that $O_2$ is a multiple context-free grammar (MCFG) were given. Such results can be exploited in the fields of both…
Evaluating Music Context Preservation: A Multi-facet Framework for Music Editing Systems
arXiv:2512.14629v2 Announce Type: replace-cross Abstract: Music editing plays a vital role in modern music production, with applications in film, broadcasting, and game development. Recent advances in music editing…
One Gate Is Not Enough: Composing Stateful Pre-Action Controls for Agentic AI
arXiv:2608.18360v1 Announce Type: cross Abstract: Agentic AI systems take consequential actions governed by more than one pre-action control at once: authority, resource, and evidence gates that can admit, degrade, or…
Accuracy and Robustness of Model Cascades Under Data Perturbations
arXiv:2608.17711v2 Announce Type: replace Abstract: Prediction cascades significantly reduce energy consumption of Artificial Intelligence (AI) models while maintaining high predictive performance. The idea is that easy…
Hybrid Reinforcement Learning and Search for Flight Trajectory Planning
arXiv:2509.04100v3 Announce Type: replace Abstract: This paper explores the combination of Reinforcement Learning (RL) and search-based path planners to speed up the optimization of flight paths for airliners, where in…
RDFdL: Integrating RDF with Differential Dynamic Logic
arXiv:2608.18165v1 Announce Type: new Abstract: Knowledge graphs modeled in RDF are powerful for describing static knowledge, but they cannot capture or reason about the dynamic behavior of physical systems, e.g.,…
Prior-Conditioned Gaussian Discriminants for Generalizable AI-generated Image Detection
arXiv:2608.18523v1 Announce Type: cross Abstract: Diffusion-based generators have made synthetic images ubiquitous, but detectors often fail under simultaneous shifts in generator, prompt/style, and source-domain. We…
OptiModNet: A UNet-Transformer Hybrid with Grouped-Query and Channel Attention for Optic Disc and Cup Segmentation
arXiv:2608.18516v1 Announce Type: cross Abstract: Precise segmentation of the optic disc and cup is critical for the early detection and diagnosis of glaucoma. However, achieving consistently high performance across…
AlphaClifford: Efficient Clifford Synthesis and Transpilation with Model-based RL
arXiv:2608.18946v1 Announce Type: cross Abstract: Clifford circuits play a foundational role in quantum computing, particularly due to their importance in quantum error correction and fault-tolerant logical synthesis.…
GS-VLA: Plug-and-Play Viewpoint Canonicalization for Frozen VLA Policies via Gaussian Splatting
arXiv:2608.19066v1 Announce Type: cross Abstract: This paper proposes a lightweight, plug-and-play framework that improves robustness to viewpoint shifts in Vision-Language-Action (VLA) policies without policy…
GrabVG: Graph-Attentive Binding for Visual Grounding in UAV Imagery
arXiv:2608.18996v1 Announce Type: cross Abstract: Visual grounding in Unmanned Aerial Vehicle (UAV) imagery aims to localize a target object in complex bird's-eye-view scenes according to a natural language description.…
Position: Profiling Game Worlds by Transition Complexity
arXiv:2608.18079v1 Announce Type: new Abstract: Game world modeling (GWM) and reinforcement learning (RL) are often confounded because research papers rarely quantify how difficult the underlying transition prediction…
ICICLE: Expanding Retrieval with In-Context Documents
arXiv:2605.26902v3 Announce Type: replace-cross Abstract: Generative retrieval (GR) maps queries directly to document identifiers (docids) using parametric knowledge, However, this design makes corpus expansion costly:…
Interpretable AI predicts a 2026 summer dry anomaly in central China
arXiv:2608.19163v1 Announce Type: cross Abstract: Seasonal precipitation anomalies are largely regulated by atmospheric circulation, which dynamical models predict with greater reliability than precipitation itself.…
Beyond the Transcript: Detecting Covert Co ordination in Latent Multi-Agent Communication
arXiv:2608.19161v1 Announce Type: new Abstract: Language-model agents can communicate through continuous hidden states that are invisible in public transcripts, creating opportunities for covert harmful coordination. We…
G-ReAct: Graph-Guided Deep Search via Structure-State Co-Evolution
arXiv:2608.01324v3 Announce Type: replace Abstract: Deep search has become a fundamental capability of large language models (LLMs) for solving open-domain complex tasks. However, existing approaches typically rely on…
The Role of Grid Cells in Reducing Spatial Aliasing in Hippocampal Place Representations
arXiv:2608.18569v1 Announce Type: cross Abstract: Spatial aliasing occurs when two or more distinct locations produce highly similar place-cell representations, primarily due to environmental symmetry or repetitive…
The Lifecycle of LLM-as-a-Judge for Large-Scale Recommendation Explanations
arXiv:2608.18300v1 Announce Type: new Abstract: LLM-as-a-Judge, which leverages a large language model to evaluate natural language generated by another AI application or model, has become a standard, scalable approach…
The Curious Case of Exploding DecPOMDPs: Containing the Fire through Policy Counting
arXiv:2608.17749v2 Announce Type: replace Abstract: Decentralised partially observable Markov decision processes (DecPOMDPs) provide a general framework for modelling multi-agent decision making under uncertainty.…
Improving Rural Medication Safety with AI: A Scoping Review
arXiv:2608.18135v1 Announce Type: new Abstract: Introduction: Medication errors (MEs) represent a significant threat to global healthcare systems, contributing to patient harm. Introducing artificial intelligence (AI)…
DELOS: Contrastive Deep Learning for Low-SNR Blind Transit Searches in Kepler Photometry
arXiv:2605.29428v3 Announce Type: replace-cross Abstract: We present DEtection in phase-folded Light curves with cOntrastive Scoring (DELOS), a deep-learning framework that uses contrastive scoring to perform blind…
From Threat Intelligence to Detection: Knowledge-driven Enrichment and Template-based Rule Grounding for Automated Sigma Rule Generation
arXiv:2608.19011v1 Announce Type: cross Abstract: Mechanisms for dynamically converting cyber threat intelligence (CTI) into actionable detection capabilities are necessary due to the rapid evolution of Advanced…
Pairwise Logical Selection of Enthymeme Completions under Semantic-Link Uncertainty
arXiv:2608.18820v1 Announce Type: new Abstract: Arguments often omit premises or claims, forming enthymemes. We study pairwise logical selection between two candidates for the omitted component. Existing natural…
Orienteering Problem with Uncertain Time-Varying Rewards: Framework and Benchmark for Everyday Service Robotics
arXiv:2608.18672v1 Announce Type: cross Abstract: We present the orienteering problem with uncertain time-varying rewards (OP-UTVR), a novel variant of the orienteering problem (OP). While most existing OP formulations…
FACET: Preserving Source Intent and Executable State in Terminal Task Synthesis
arXiv:2608.18580v1 Announce Type: new Abstract: Training terminal agents requires scalable executable supervision, yet synthesizing high-quality terminal tasks remains challenging. Each task couples an instruction, an…
When Clean Signals Are Not Enough: Detecting Structural Ambiguity for Safe Wearable Stress Classification
arXiv:2608.18397v1 Announce Type: new Abstract: Wearable stress classifiers can achieve strong average performance while failing completely for a particular individual. On WESAD, a Random Forest reaches 93.0% mean…
Solving Is Not Drawing: A Benchmark for Diagrammatic Reasoning in Olympiad Geometry
arXiv:2608.18111v1 Announce Type: new Abstract: Foundation models such as GPT and Claude now solve olympiad-level mathematics with remarkable proficiency, so much so that geometry problem solving has become a standard…
TrojanGYM: A Detector-in-the-Loop LLM for Adaptive RTL Hardware Trojan Insertion
arXiv:2601.17178v3 Announce Type: replace-cross Abstract: Hardware Trojans (HTs) remain a critical threat because learning-based detectors often overfit to narrow trigger/payload patterns and small, stylized benchmarks.…
Position: Behavioral Systems Require Behavioral Tests
arXiv:2608.18081v1 Announce Type: new Abstract: Artificial agentic systems increasingly operate as behavioral systems by interacting with dynamic environments, pursuing goals, and adapting over time. Yet, current…
VibeWorlding: Can Multimodal Agents Construct 3D Open Worlds End-to-End?
arXiv:2608.15265v2 Announce Type: replace Abstract: Constructing an interactive 3D open world from a user query is important. However, existing methods are primarily evaluated on idealized, simple queries, making it…
Self-Evolving Agents as Dynamic Graph Transformation: A Survey and New Perspective
arXiv:2608.18104v1 Announce Type: new Abstract: Large language model (LLM)-based agents are increasingly becoming self-evolving systems that persist across interactions, maintain memories, use tools, acquire skills,…
ADEPT: Accelerating Dexterity via Pre-Training and Post-Training using Reinforcement Learning
arXiv:2608.19182v1 Announce Type: cross Abstract: We introduce Accelerating Dexterity via Pre-Training (ADEPT), a large-scale reinforcement learning (RL) framework for learning sim-to-real transferable dexterity across…
GRIP: Grounded Reasoning via Information-Restricted Premises
arXiv:2608.16776v2 Announce Type: replace Abstract: High-capacity encoders in retrieval-augmented generation (RAG) can let the query dominate the latent state, leaving retrieved evidence functionally irrelevant. We call…
Admission Without Answers: Label-Free Certification and Experience Learning for LLM-Based Optimization Modeling
arXiv:2608.15565v3 Announce Type: replace Abstract: Experience-learning agents for optimization modeling improve by storing verified skills, but existing learners admit knowledge by checking against known answers, which…
Event-Causal RAG: A Retrieval-Augmented Generation Framework for Long Video Reasoning in Complex Scenarios
arXiv:2605.06185v2 Announce Type: replace Abstract: Large vision-language models perform well on short- and medium-length video understanding but still struggle to maintain coherent event memory and recover long-range…
FairGlucose: A CGM Fairness Benchmark Reveals Subgroup Disparities Hidden in Population-Level Validation
arXiv:2608.18296v1 Announce Type: cross Abstract: As CGM-based AI tools approach clinical deployment, whether their accuracy is equitable across patient demographics remains insufficiently tested. To enable this…
Hybrid ANN-SNN Pipeline with Local Plasticity
arXiv:2606.20151v2 Announce Type: replace-cross Abstract: This work proposes a hybrid ANN-SNN pipeline that effectively leverages the rich embeddings of pretrained artificial neural networks (ANNs) to enable…
Teaching agentic AI to learn expert reasoning for rare disease diagnosis
arXiv:2606.16149v4 Announce Type: replace Abstract: Rare disease diagnosis depends on expert reasoning that is scarce and difficult to transfer; off-the-shelf large language models (LLMs) rank the correct disease first…
Low-Rank Dynamics-Effective Latent Carriers for Counterfactual Rollout in Learned World Models
arXiv:2608.15156v2 Announce Type: replace-cross Abstract: World models may predict the future without making clear which parts of their hidden state actually drive those predictions. We ask whether a small, directly…
LEDGER: Claim-to-Evidence Trace Graphs for Auditing LLM Agents
arXiv:2608.18398v1 Announce Type: cross Abstract: Large language model (LLM) agents can now carry out long-horizon technical workflows involving complex tool use, code execution, file edits, and generated artifacts. As…
Formal Verification of Romanov's Triplet Logic: A Verified Filter for Sliding-window 3-CNF with Application to Structured Formulas
arXiv:2608.18445v1 Announce Type: cross Abstract: We present the first mechanised formalisation of Romanov's Triplet Logic (TLS) in the Rocq proof assistant. TLS is a triplet-based combinatorial framework for reasoning…
The Epistemic Politics of AI Anthropomorphism
arXiv:2608.00961v3 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…
Governance Records as Supervision: Verifier-Selected Self-Training for Structured Workflow Repair
arXiv:2608.18324v1 Announce Type: new Abstract: Machine-verifiable workflows produce governance records linking a task contract, model attempt, verifier decision, accepted output, and target origin. We test whether…
Epistemic Subordination: Generative AI and the Infrastructure of Knowledge
arXiv:2608.18758v1 Announce Type: cross Abstract: Generative AI does not merely produce biased outputs. It encodes the majority's way of knowing as the default infrastructure of knowledge itself. We call this epistemic…
Verifiable abstention makes AI leak diagnosis accountable in water distribution networks
arXiv:2608.18836v1 Announce Type: new Abstract: Utilities lose a substantial share of treated water to leakage, yet rarely trust artificial-intelligence localizers to dispatch crews: guessing everywhere cannot justify…
Syntactic Simplification of OWL Class Expressions
arXiv:2608.18899v1 Announce Type: new Abstract: Class expression learning often produces complex OWL class expressions that are difficult to interpret and reason over. However, by following theoretically grounded…
Planning-aligned Token Compression for Long-Context Autonomous Driving
arXiv:2606.07464v3 Announce Type: replace-cross Abstract: Monolithic vision-action models represent an emerging paradigm in autonomous driving. However, this architecture produces token sequences that quickly exceed…
GenEx: A Graph-Based Representational Paradigm for SARS-CoV-2 Variant Detection via Codon Co-occurrence Networks
arXiv:2608.18238v1 Announce Type: new Abstract: Genomic analysis on viruses such as SARS-CoV-2 variants: Beta, Gamma, Delta, and Omicron is heavily dominated by classical bioinformatics methods, including Sequence…
SIDScope: A Diagnostic Resource for Semantic-ID Interfaces in Generative Recommendation
arXiv:2608.18779v1 Announce Type: cross Abstract: Semantic-ID mappings are reusable interfaces between item tokenizers and generative recommenders, yet released mappings rarely state whether they are coherent, what…
BrainWAM: Action-Space Coordination of Semantic Priors and Predictive Dynamics for Autonomous Driving
arXiv:2608.12854v2 Announce Type: replace-cross Abstract: Autonomous driving requires planning under both semantic constraints and predictive dynamics. Existing end-to-end driving approaches, however, typically…
Counterfactual Contrastive Analysis
arXiv:2608.19032v1 Announce Type: cross Abstract: Visual Counterfactual Explanations (VCEs) aim to explain image classifiers by generating minimally edited and realistic versions of an input image that change the…
Sleeping Kelly
arXiv:2510.15911v4 Announce Type: replace-cross Abstract: The Sleeping Beauty problem is a problem of imperfect recall that has received considerable attention. One approach to resolving the Sleeping Beauty problem has…
DA-WAM: Decision-Aligned Future Latents for Driving World Models
arXiv:2608.19085v1 Announce Type: cross Abstract: Anticipating how scenes evolve under ego actions is fundamental to safe autonomous driving, yet the full potential of world models for decision-making remains…
Fragility of Value under Imperfect Alignment
arXiv:2607.28881v3 Announce Type: replace Abstract: As more responsibility is placed upon AI systems, it becomes increasingly important to guarantee that these systems are aligned with humanity. A common fear in AI…
SeisEvo: Evolution of Seismic Data Reconstruction Algorithms by Agents
arXiv:2608.18272v1 Announce Type: cross Abstract: Classical seismic data reconstruction relies on manually designed structural priors and iterative operators, whose coupled design space is far larger than manual trial…
Sanyu Studio: A Multi-Agent System for Art-Historical Narrative Construction
arXiv:2608.18677v1 Announce Type: new Abstract: Amid concerns that generative AI may standardize art interpretation, this paper examines whether LLM-based interaction can support plural art-historical narrative…
CentaurBench: Benchmarking LLM Capabilities on Augmenting vs. Automating Real-World Work Tasks
arXiv:2608.18554v1 Announce Type: cross Abstract: Most LLM benchmarks rank models on their ability to automate work tasks. In practice, however, models are often used to assist other (human or LLM) agents. The question…
Optimized Fuzzy Logic Approach with the IEEE Key Gas Method for Diagnosing Power Transformer Faults Using Dissolved Gas Analysis
arXiv:2608.18133v1 Announce Type: new Abstract: Reliable transformer fault diagnosis is essential for maintaining power system stability. The IEEE Key Gas Method (KGM), a widely utilized approach in Dissolved Gas…
RTPO: Reverse-Turn Policy Optimization for Stabilizing Agentic RL Training
arXiv:2608.18682v1 Announce Type: new Abstract: Training multi-turn agentic workflows with reinforcement learning (RL) enables large language models to perform complex reasoning, use external tools, and conduct…
A Metamorphic Artificial Age Score Decision-Support Prototype for Flight-Log-Based Drone Propeller Health Monitoring
arXiv:2608.18088v1 Announce Type: new Abstract: Drone propeller faults can create safety and reliability risks when their effects are distributed across multiple flight-log channels rather than appearing as a single…
Tuning the Stochastic Machine: A Systems Engineer's Operating Model for Human-AI Engineering
arXiv:2608.19125v1 Announce Type: new Abstract: When an expert corrects an LLM assistant's error, the correction usually dies with the session, and the error class returns. I argue this is an operations problem, not a…
Finetuning Strategies for Querying Sounds by Vocal Imitation
arXiv:2608.19174v1 Announce Type: cross Abstract: This technical report describes our winning submission to the AES AIMLA 2025 Challenge on querying sound effects by vocal imitation. We investigate two complementary…
Large Language Model for Verilog Code Generation: Literature Review and the Road Ahead
arXiv:2512.00020v3 Announce Type: replace-cross Abstract: Code generation has emerged as a critical research area at the intersection of Software Engineering (SE) and Artificial Intelligence (AI), attracting significant…
RULER: Representation-Level Verification of Machine Unlearning
arXiv:2605.27569v3 Announce Type: replace Abstract: Machine unlearning aims to remove the influence of specific training records from a deployed model without retraining from scratch. Current protocols verify this at…
One-Stage Object Detectors in Autonomous Driving
arXiv:2608.19014v1 Announce Type: cross Abstract: Autonomous vehicles depend on fast and reliable perception systems to detect surrounding vehicles, pedestrians, cyclists, traffic signs, and other road objects in real…
How AI Prompts Can Teach Us About the Structure of Human Behavior
arXiv:2608.18265v1 Announce Type: cross Abstract: We introduce a general, easy-to-implement AI-based method for studying the structure and complexity of human behavior. We assign a large language model a ``type vector''…
UMER: Unifying Embedding and Ranking via Pair-Aware Discriminative Reasoning for Universal Multimodal Retrieval
arXiv:2608.18504v1 Announce Type: new Abstract: Universal multimodal retrieval aims to support diverse instruction-aware retrieval tasks, demanding both efficient corpus-scale matching and fine-grained semantic…
ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System
arXiv:2607.14178v3 Announce Type: replace Abstract: Recent advances in Large Language Models have fueled autonomous AI agents capable of tackling complex scientific tasks, yet existing automated research systems remain…