Measuring the Creativity Potential of LLM Agents
Trying to answer the question of "Can LLM agents discover?" through the lens of creativity The post Measuring the Creativity Potential of LLM Agents appeared first on Towards Data Science.
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How to Use a PINN for a Navier-Stokes Inverse Problem
A from-scratch PyTorch build that recovers blood flow, viscosity, and wall shear stress in a narrowed artery from 40 noisy velocity readings The post How to Use a PINN for a Navier-Stokes Inverse Problem appeared first…
CompactionRL: Reinforcement Learning with Context Compaction for Long-Horizon Agents
arXiv:2607.05378v2 Announce Type: replace Abstract: Long-horizon agentic LLMs are increasingly limited by finite context windows, as extended interaction trajectories can exceed the maximum context length before a task…
Sharpening Tax in Post-Training
arXiv:2610.01509v1 Announce Type: cross Abstract: An emerging hypothesis about reinforcement learning (RL) post-training of large language models (LLMs) is that it merely sharpens existing behaviors of a base model,…
Evidence-Gated Research: Statistically Controlled Model Adoption in Adaptive Search
arXiv:2610.01751v1 Announce Type: new Abstract: Adaptive model search is path dependent: once a challenger is adopted, it becomes the reference from which later candidates are generated. A statistically unsupported…
ROGUE: Evaluating Corrigibility Failures in Frontier Computer-Use Agents
arXiv:2606.00341v2 Announce Type: replace Abstract: As AI agents are increasingly deployed in real personal and corporate settings (email accounts, development workflows, company databases, etc.), safety considerations…
Multi-User mmWave Beam and Rate Adaptation via Combinatorial Satisficing Bandits
arXiv:2604.14908v2 Announce Type: replace Abstract: We study downlink beam and rate adaptation in a multi-user mmWave MISO system where multiple base stations (BSs), each using analog beamforming from finite codebooks,…
Exact Distinguishability in Non-Markovian Decision Processes
arXiv:2610.01527v1 Announce Type: new Abstract: Non-Markovian environments are often modeled as Regular Decision Processes (RDPs), where dynamics depend on the interaction history through a finite automaton. Existing…
Posterior sampling by source-space MCMC via prior-based few-step transport maps
arXiv:2610.01034v1 Announce Type: cross Abstract: Bayesian inference increasingly uses informative but implicit priors represented only by samples, such as historical ensembles, simulator outputs, and pretrained…
Temporally-Resolved Token Attribution Reveals the Generation Dynamics of Diffusion Language Models
arXiv:2610.01177v1 Announce Type: cross Abstract: This work presents Diffusion Layer Integrated Gradients (DLIG), a token attribution method for diffusion language models (DLMs) that extends Integrated Gradients…
FourierQK: Filter Shape, Admissibility and the Leakage-Coverage Law
arXiv:2610.00009v1 Announce Type: new Abstract: Frequency-collapse attention [Zeris, 2026e] achieves large gains over standard dot-product attention by replacing the Q/K dot product with a bandpass-filtered inner…
Redundancy Meets Synergy: Dependency-aware Expert Selection for MoE via Submodular Optimization
arXiv:2610.00558v1 Announce Type: new Abstract: While Mixture-of-Experts (MoE) models effectively scale model capacity through sparse activation, their deployment is often bottlenecked by prohibitive memory…
Stochastic Optimal Control for Continuous-Time fMRI Representation Learning
arXiv:2502.04892v2 Announce Type: replace Abstract: Learning robust representations from functional magnetic resonance imaging (fMRI) is fundamentally challenged by the temporal irregularity and noise inherent in data…
Asynchronous LLM Post-Training: Group-Mass Capping and Convergence Analysis
arXiv:2610.01896v1 Announce Type: new Abstract: Asynchronous reinforcement learning (RL) improves the efficiency of large language model post-training but introduces stale rollouts generated by earlier policies.…
Robust Is Salient: An Informed Adversary Moves the Optimal Signal onto the Salience Pole
arXiv:2610.00233v1 Announce Type: cross Abstract: When an informed adversary shares the audience of a constrained signalling channel, the signal that best protects the truth is the signal that best describes it. On 108…
ReHoPER: Receding-Horizon Planning for Enhanced Reasoning
arXiv:2610.00940v1 Announce Type: cross Abstract: We propose ReHoPER, an inference-only, zero-shot method that improves large language models' reasoning by generating and answering intermediate questions along multiple…
CF-JEPA: Improving Robustness of JEPA World Models via Controllability Factorization
arXiv:2610.00727v1 Announce Type: cross Abstract: Controlling an agent with vision requires being able to separate useful information from irrelevant background information. JEPA-style latent world models seem like a…
Actions with Receipts: Jointly Binding Claims, Evidence, and Execution for Replayable Tool-Agent Auditing
arXiv:2610.00327v1 Announce Type: cross Abstract: Tool-using agents can expose citations and execution logs while leaving a critical association unaudited: whether the claim shown to a user is the claim emitted by the…
SHARPO: Segment-Level Credit Assignment for Agentic Reinforcement Learning
arXiv:2610.00838v1 Announce Type: new Abstract: Agentic reinforcement learning (RL) trains a large language model (LLM) to act over long, multi-step interactions. However, a single localized error can cause task…
Artifact Annotations Partially Substitute for Per-User Calibration: SAFE-EDA and a Normalization-Controlled Evaluation of Wrist-EDA Affect Recognition
arXiv:2610.01692v1 Announce Type: new Abstract: Wrist electrodermal activity (EDA) differs in amplitude from one person to the next, so affect-recognition models normalize their input before classification. Studies that…
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