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Artificial Intelligence
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The newest 5,000 papers, from 11 October 2026 to 5 November 2026: 4,993 arXiv preprints and 7 OpenAlex records.
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Newest papers, page 32
Auditing Representation-Space Fraud Detection: A Bayesian IRL Framework for Calibrated Uncertainty and Its Limits
Shilling detectors for recommender systems are almost always evaluated by one number, detection AUROC, with no account of when it can be trusted.Reap: Uncovering Monte Carlo proof search with a lightweight model
We present Reap, an open framework for learning and analyzing formal proof search in Lean4.VioTech: Frame-Level Violin Playing Technique Detection with Multi-Scale Mixture-of-Experts
Playing technique is crucial for expressive violin performance, yet few violin technique detection models exist.HistoTx: Early fusion of H&E images and spatial transcriptomics at varying spatial transcriptomics resolution with self-supervised learning
Spatial transcriptomics maps gene expression across tissue sections and, when integrated with whole slide images, jointly captures both morphological architecture and molecular activity to provide a…Accelerating LLM Pretraining with Zeroth-Order Curvature on Idle Serving Compute
LLM pretraining is increasingly compute-intensive, while substantial inference serving compute remains idle during off-peak periods.The Customer Never Sees the Goal: Measuring and Detecting Vulnerability-Targeted Manipulation in LLM Assistants
Companies deploy large language model (LLM) assistants on their websites to advise customers.Human-Oriented World Model
Supporting a person over repeated interactions requires interpreting their current state in context and anticipating its subsequent evolution.Closing the Dynamics Gap through Self-Directed Robotic Interaction
Agentic Real2Sim2Real systems can reconstruct a scene in simulation from camera observations, but contact-rich dynamics such as friction and restitution cannot be observed without interaction.GeoGuesser Bench: Benchmarking Vision-Language Agents on Interactive Geolocation
Vision-language model (VLM) agents that act in the open world need two abilities: world knowledge to interpret what they see, and exploration to find what they cannot yet see.Beyond Answers, Traces, and Efficiency: Evidence for Adaptive Reasoning
Current AI systems are evaluated as reasoners through final-answer accuracy, reasoning traces, process supervision, and computational or human-relative efficiency.Hindsight Credit Assignment over Trees for Agentic RL
Reinforcement learning for long-horizon LLM agents faces a fundamental dilemma: successful experiences are essential for policy improvement, yet limited policy capabilities make such experiences…Human-Supervised Artificial Intelligence Researchers in Electric Power Systems: Knowledge, Physics, Simulation, and Governance for Large Language Models
Conclusions in power-system research require a clear evidential basis.MURFormer: Attention-Based Lightweight Multi-Scale Uncertainty-Guided Refinement Framework for PPG Denoising
Photoplethysmography (PPG) is a widely used physiological signal for its convenience but is highly susceptible to motion artifacts that degrade waveform quality and limit downstream analysis.IssueLighter: An Issue Type-Aware LLM Agent for Issue Report Validity Assessment
Invalid issue reports are prevalent in open source software (OSS) projects, imposing substantial burdens on maintainers who already face a high risk of burnout.AffToM: Benchmarking Recursive Affective Theory of Mind in Dynamic Multi-Party Interactions
Understanding emotion in realistic social interactions requires more than recognizing facial expressions or assigning affective labels.MoviEdit: Long-form Multi-Shot Video Editing Made Easy
Long-form multi-shot video editing requires an intended edit to remain coherent across abrupt changes in scene, viewpoint, and subject appearance, while processing substantially longer visual…What Drives the Zero-to-One Jump? Diagnosing and Steering Hard-Prompt Learning in RLVR
Reinforcement Learning with Verifiable Rewards (RLVR) has substantially improved mathematical reasoning, yet progress on hard prompts often stalls: a prompt can remain unsolved for many training…Investigating the effects of the patch size in Time Series Foundation Models
Patch size is a central design choice in patch-based time-series foundation models, controlling temporal resolution, sequence length, and computational cost.DINOFAS: Bonafide-Centric Representation Learning for Face Anti-Spoofing
Face anti-spoofing (FAS) models often learn attack- and dataset-specific cues that degrade performance under unseen acquisition conditions and presentation attacks.Is your LLM an Agressive Narcissist with Depression? Analyzing Psychological Portraits of Large Language Models
Nowadays, interaction with AI requires caution not only regarding the factual reliability of generated content but also regarding personality markers that models may implicitly transmit during…