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Artificial Intelligence
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The newest 5,000 papers, from 11 October 2026 to 5 November 2026: 4,998 arXiv preprints and 2 OpenAlex records.
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Newest papers, page 161
From Trace to Fix: Residual Task State in Long-Horizon Agents
Recovering from failures in long-horizon, stateful language agents is challenging because the action introducing a defect, the symptom exposing it, and the persistent state requiring repair…Standing on the Shoulders of Giants: Enhancing LLM Agents for Automated Fact-Checking with Human Expert Skills
Automated fact-checking (AFC) systems powered by large language model (LLM) agents still face challenges in evidence retrieval and claim verification.OpenSaC: A Python Library for Search as Code in Deep Research Agents
Deep research agents investigate complex questions through iterative search, source examination, and evidence synthesis.Can LLM User-Proxies Stand In for Humans in Reliance Measurement? Replicating Rel-A.I. with Simulated Users
Can language-model user proxies reproduce human reliance on an AI answer across contexts?SAR: Learning Global Item-Space Matching and Geometry-Aware Placement Ranking for Buffered Online 3D Bin Packing
Online 3D bin packing with a bounded buffer requires irreversible item-selection and placement decisions under limited knowledge of future arrivals.AirMPA: A Meteorology-to-Pollution Adapter for Global Air Quality Forecasting
Accurate real-time forecasting of atmospheric pollutants is essential for reducing exposure risks and improving public health.When to Stop Asking: Factor Coverage Bias and LLM Determinability Judgments with Underspecified Information in Medicine
Clinical decision-making often begins with underspecified information and requires not only gathering missing information but also knowing when to stop.Optimizing Marketing Budgets for Social Influence: A Generalized Fractional Incentives Framework
Marketing managers routinely allocate limited budgets across individuals in social networks whose responsiveness and influence vary substantially.When Retrieval Partially Conflicts with Skills: Understanding Procedural Hallucination in Language Models
Language models increasingly use skills that provide reusable instructions and procedures for task execution.FrontierRefactor: Benchmarking Multi-Scale Performance-Oriented Codebase Refactoring
Autonomous codebase refactoring requires coding agents to restructure working software while strictly preserving externally observable behavior and prioritizing execution performance and compute…Diffusion Language Models Change Speed Across Tasks and Languages
Diffusion language models can write several tokens in one forward pass, and they decide during generation how many passes to spend.Where RL Breaks: Localizing and Repairing Failures via Targeted Continued Pretraining
Reinforcement learning with verifiable rewards (RLVR) is widely used to improve reasoning in language models, yet growing evidence suggests that it mostly sharpens what the base model can already do.OV-PEAR: Observation-Verified Pose-Scale Estimation and Reconstruction for Unknown Industrial Manipulation Objects
Fine industrial robotic manipulation requires 6D pose, scale, and an operation-ready 3D model.Not Every Rollout Needs Distillation: Correctness-Filtered On-Policy Self-Distillation
On-policy self-distillation (OPSD) supervises student-generated trajectories with a reference-conditioned version of the same base model.A Cue's Hidden Price: Auditing Seller Influence on AI Shoppers
Large language models are increasingly asked to shop on a user's behalf, which lets seller-controlled content such as badges, endorsements, and framing steer what they recommend.SWIFT: Self-guided Weak-to-strong dIFfusion models via Target extrapolation
Training high-quality diffusion models is computationally expensive, and inference-time guidance often adds further sampling cost.Measurement Validity and Representation Dynamics of Confidence Signals in Large Language Models
Whether a language model "knows what it knows" matters for trustworthy deployment and for deciding when it should abstain.Rubrics Beyond Evaluation: Exploiting Rubric Structure in Reinforcement Learning
Rubrics are widely used to evaluate open-ended question answering by breaking overall quality into explicit criteria.MASIF: Implicit Failures for Process Observability in Multi-Agent Systems
Multi-agent systems (MAS) can complete a task despite local execution errors that are corrected, bypassed, or carried forward without individually determining its outcome.Are Self-Evolving Agents Continual Learners?
Large language model agents are often deployed in environments where new knowledge, tools, and workflows keep arriving.