AI news archive.
4,966 articles filed under Agents, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsMemento 3: Model-Based Recursive Self-Improvement through Reflective Rulebooks
arXiv:2610.11794v1 Announce Type: new Abstract: Learning to act in unfamiliar environments requires agents to infer how the world works and revise that understanding as new evidence arrives. Yet limited observations can…
- arXiv cs.AIagentsWhen Should Agents Think? Adaptive Reasoning via Cross-Turn Estimation
arXiv:2610.12061v1 Announce Type: new Abstract: Large language model (LLM)-based agents have demonstrated strong capabilities on complex tasks. They typically perform reasoning before each action throughout an interactio…
- arXiv cs.AIagentsEvoAlloc: A Self-Evolving Resource Allocation Agent for Efficient Program Evolution
arXiv:2610.12086v1 Announce Type: new Abstract: LLM-based program evolution relies on evaluation feedback to guide the iterative search for high-performing programs. However, evaluation is often computationally expensive…
- arXiv cs.AIagentsUse and Disuse: Intent-Structured Experience Consolidation for Memory and Learning in LLM Agents
arXiv:2610.12124v1 Announce Type: new Abstract: The evolution of Large Language Model agents from single-task execution to long-term autonomous operation highlights the critical challenge of transforming continuous exper…
- arXiv cs.AIagentsOA-MAP: Evidence-Grounded Multi-Agent Multimodal Framework for Interpretable Knee Osteoarthritis Progression
arXiv:2610.12134v1 Announce Type: new Abstract: Knee osteoarthritis (KOA) progression prediction can support patient monitoring, requiring the integration of multimodal data and multidomain expertise. Moreover, isolated…
- arXiv cs.AIagentsQ-Shaped Options for Hierarchical Reinforcement Learning
arXiv:2610.12135v1 Announce Type: new Abstract: Learning to tackle long-horizon, goal-conditioned tasks requires an agent to reason over extended timescales and act across a broad range of states. In principle, Hierarchi…
- arXiv cs.AIagentsRecursive Self-Improvement through Multi-Agent Self-Supervision
arXiv:2610.12176v1 Announce Type: new Abstract: Recursive self-improvement (RSI) of a model on non-verifiable tasks, such as open-ended research, faces a supervision bottleneck when its outputs exceed what even human exp…
- arXiv cs.AIagentsOne Word Opens the Gate: The Option-Channel Attack on Typed Decision Models as Agent Guardrails
arXiv:2610.12292v1 Announce Type: new Abstract: A typed decision model reads a piece of text and returns a probability over caller-defined options, each with a short written definition, generating no text. Recent work pl…
- arXiv cs.AIagentsPrior or Feedback? What an LLM Uses When Adapting Neural Operators
arXiv:2610.12325v1 Announce Type: new Abstract: Do LLM scientific agents rely only on their initial task context, or do they adapt their decisions in response to experimental feedback? We study this question in neural op…
- arXiv cs.AIagentsCan AI Agents Learn Their Way to the Top? Evaluating Heuristic Learning in a Long-Running Game Agent Competition
arXiv:2610.12341v1 Announce Type: new Abstract: Adversarial games have driven advances from heuristic search to reinforcement learning, yet learning and adapting strategies from limited samples remain challenging. AI age…
- arXiv cs.AIagentsAccurate but Not Humble: Evaluating Epistemic Humility in LLM Agents under Knowledge Conflict
arXiv:2610.12360v1 Announce Type: new Abstract: When retrieved evidence contradicts an agent's prior beliefs, does it revise its answer, acknowledge uncertainty, or persist with an incorrect conclusion? Existing evaluati…
- arXiv cs.AIagentsOnTrack: Real-Time Monitoring and Intervention in LLM Agent Trajectories via Streaming Structure-Aware Optimal Transport
arXiv:2610.12375v1 Announce Type: new Abstract: Agents are deployed in applications from trip planners and stock trading to IT incident triage. In most cases, LLM agents work autonomously with minimal rule-based safeguar…
- arXiv cs.AIagentsEcology of AI Agents: Collaboration Creates a Population Threshold for Takeoff
arXiv:2610.12436v1 Announce Type: new Abstract: AI agents can now conduct real-world cyberattacks, scale up capabilities with the number of agents, and collectively pursue misaligned goals to obtain rewards. Together, th…
- arXiv cs.AIagentsBrickBench: Evaluating Agentic Brick Design
arXiv:2610.12452v1 Announce Type: new Abstract: We propose BrickBench, a benchmark for agentic text-conditioned LEGO-set design. Given a prompt, an agent is tasked with producing an assembly that not only satisfies seman…
- arXiv cs.AIagentsBeyond Type-checking: Towards Holistic Evaluation of Formal Specification Generation
arXiv:2610.10604v1 Announce Type: cross Abstract: When generating verifiable code, natural language requirements are mapped to machine checked code using LLMs and agentic workflows. A crucial component of this pipeline i…
- arXiv cs.AIagentsFrom Investigation Failures to Reliable SOC Agents: Understanding and Improving LLM-Based Alert Triage
arXiv:2610.10608v1 Announce Type: cross Abstract: Security operations centers (SOCs) must triage large volumes of alerts, most of which are benign, while missed attacks can remain uninvestigated. Tool-using large languag…
- arXiv cs.AIagentsCode Understanding is a Bottleneck for Coding Agents
arXiv:2610.10610v1 Announce Type: cross Abstract: Repository benchmarks (e.g., SWE-bench) for coding agents often assume that lines of code edited can predict task difficulty, but such datasets' poor control over code an…
- arXiv cs.AIagentsTestJack: Should you trust the results in coding benchmarks? Agentic Coding Benchmarks Auditing via Evaluator Evolution
arXiv:2610.10619v1 Announce Type: cross Abstract: Large language model (LLM) agents are rapidly reshaping software engineering, accompanied by an explosion of new code benchmarks. Yet nearly all existing benchmarks still…
- arXiv cs.AIagentsWhen AI Finds Hidden Messages, Does It Report?
arXiv:2610.10620v1 Announce Type: cross Abstract: When an assistant encounters a message for another AI, does it tell its user? Four fixed model-provider deployments perform simulated source tasks in 1,280 ordinary-note…
- arXiv cs.AIagentsAgent4RE: A Self-Refining Multi-agent Framework for End-to-End Software Requirements Engineering and Benchmarking
arXiv:2610.10628v1 Announce Type: cross Abstract: Existing LLM-based approaches for software Requirements Engineering (RE) typically rely on basic prompting strategies or rudimentary agent collaboration, under-utilizing…
- arXiv cs.AIagentsMemoWM: How World Models Change What Agents Need to Remember
arXiv:2610.10778v1 Announce Type: cross Abstract: Long-term agents face growing storage demands as they accumulate experience. World models capture reusable regularities that can reduce the information stored for each ex…
- arXiv cs.AIagentsNavGPT-3: Harnessing Context in a Hierarchical Navigation Runtime
arXiv:2610.10787v2 Announce Type: replace-cross Abstract: Language models trained with long-horizon agentic reinforcement learning can generalize knowledge through reasoning, express precise actions, and pursue goals ove…
- arXiv cs.AIagentsRFChipAgent: Multi-Agentic AI Flow for Analog/RF Chip Design
arXiv:2610.10858v1 Announce Type: cross Abstract: Analog/RF circuits remain the critical interface between digital computation and the physical world, and emerging standards from Wi-Fi 7 to 6G place stringent demands on…
- arXiv cs.AIagentsStochastic Teacher Intervention for Agentic On-Policy Distillation
arXiv:2610.10878v1 Announce Type: cross Abstract: On-policy distillation (OPD) efficiently transfers capabilities from a stronger teacher to a student language model through dense token-level supervision on student-gener…
- arXiv cs.AIagentsCross-Provider Review as a Runtime Contract for Coding Agents: A Controlled Pilot and Fault-Injection Study
arXiv:2610.10961v1 Announce Type: cross Abstract: Coding agents increasingly share a workstation while drawing on separate providers and subscription allowances. A second agent can inspect a completed answer, but the cal…
- arXiv cs.AIagentsiAm.md: Robot Skill Self-Assessment through Agentic Introspection for Unknown Open-Vocabulary Domains
arXiv:2610.10962v1 Announce Type: cross Abstract: Agentic AI based on Large Language Model generalization capabilities offers a wide range of potential applications, including planning for embodied tasks. For example, em…
- arXiv cs.AIagentsWhy LLM Agents Favor Their Group: Stakes, Observed Norms, and Reputation
arXiv:2610.11008v1 Announce Type: cross Abstract: Language-model agents favor their own group because they have watched their members favor each other. The group label alone does little once the decision has a cost; what…
- arXiv cs.AIagentsNOMOS: Compiling Written Policies into Statically Verified Tool-Call Gates for LLM Agents
arXiv:2610.11030v2 Announce Type: replace-cross Abstract: Tool-using LLM agents violate the policies they are deployed to enforce, often silently. Prior defenses hand-write rules, query an LLM verifier per action, or com…
- arXiv cs.AIagentsAffordDrive3D: Affordance-Aware World-Action Modeling with Spatial Understanding
arXiv:2610.11060v2 Announce Type: replace-cross Abstract: World-action models have recently improved autonomous driving by jointly learning future scene prediction and trajectory generation. Most existing approaches mode…
- arXiv cs.AIagentsActiveMedAgent: Cost-Aware Trajectory Learning for Multimodal Medical Diagnosis
arXiv:2610.11140v1 Announce Type: cross Abstract: Clinical diagnosis is inherently sequential: clinicians escalate from cheap to costly tests only when additional evidence is expected to resolve diagnostic uncertainty. W…
- arXiv cs.AIagentsVAMR: Multi-Question Agentic Reasoning for Efficient Long-Form Video Understanding
arXiv:2610.11171v1 Announce Type: cross Abstract: Long-form video understanding often involves multiple questions about different aspects of the same recording. Yet existing video agents typically process each question t…
- arXiv cs.AIagentsREMORY: Learning Residual Memory for Context Compaction
arXiv:2610.11287v3 Announce Type: replace-cross Abstract: Long-horizon agents compact their history to continue within a finite context window, but a textual summary alone may not support every subsequent decision. We in…
- arXiv cs.AIagentsClosed-loop evaluation of LLM agents for embedded software development
arXiv:2610.11447v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as coding agents that edit files, run builds and tests, inspect execution results, and repair software iteratively.…
- arXiv cs.AIagentsGROB: A Multi-Agent Architecture for Public-Trace Investigation of Candidate Agentic Activity
arXiv:2610.11467v1 Announce Type: cross Abstract: We present GROB, a multi-agent architecture for investigating candidate autonomous-agent activity through public Internet traces when privileged telemetry is unavailable.…
- arXiv cs.AIagentsRoboAware: Learning to Coordinate Embodied Skills from Counterfactual Outcomes
arXiv:2610.11480v1 Announce Type: cross Abstract: Embodied coding agents can combine modular robot skills with frozen end-to-end policies, yet effective composition requires anticipating which policy family will succeed…
- arXiv cs.AIagentsEvaluating Local Language Model Agents for Reproducible Data Engineering: An Empirical Software Engineering Study of Mobility Workflows
arXiv:2610.11482v1 Announce Type: cross Abstract: Context: Large language model (LLM) agents are increasingly used as software and data-engineering assistants, yet evidence about locally deployable open-weight agents rem…
- arXiv cs.AIagentsConstitutional Gating and Deterministic Recovery for Multi-Agent LLM Negotiation: Ablations Against a Stateful Adversarial Gatekeeper
arXiv:2610.11542v3 Announce Type: replace-cross Abstract: Multi-agent LLM systems negotiating with a stateful counterpart waste model calls in three ways: polite loops that never meet the counterpart's hidden acceptance…
- arXiv cs.AIagentsSWE-Journey: Towards More Realistic Evaluation of Coding Assistants through Long-Horizon, Multi-Turn Interaction
arXiv:2610.11559v1 Announce Type: cross Abstract: Coding assistants such as Claude Code and Codex have become a major application of LLM agents, yet existing benchmarks remain far from real-world use, particularly in tas…
- arXiv cs.AIagentsSDPAD: A Fully Spike-Driven Pipeline for End-to-End Autonomous Driving
arXiv:2610.11583v1 Announce Type: cross Abstract: End-to-end autonomous driving demands trajectory planners that are both highly accurate and cheap enough for edge deployment. State-of-the-art artificial neural network (…
- arXiv cs.AIagentsRunnable Commit Untangling for Coding Agents
arXiv:2610.11593v1 Announce Type: cross Abstract: Coding agents produce large, tangled patches that mix multiple development purposes, making the code hard to review and maintain. Commit untangling offers the promise of…
- arXiv cs.AIagentsOne Skill Too Many: How Co-Installed Skills Conflict in Coding Agents
arXiv:2610.11647v2 Announce Type: replace-cross Abstract: Coding agents are extended with agent skills, directories whose SKILL.md tells the model when and how to perform a task. Because skills come from independent sour…
- arXiv cs.AIagentsSkillContrast: Difference-Guided Text Selection for Agent Skill Reranking
arXiv:2610.11650v1 Announce Type: cross Abstract: Similar agent skills can share instructions but differ in their conditions of use. Query-based text selection may retain shared instructions and omit these distinctions.…
- arXiv cs.AIagentsNarrow and Deep: An Ontology Tower as the Knowledge of an LLM Agent for an Industrial Equipment System
arXiv:2610.11768v1 Announce Type: cross Abstract: Large language model (LLM) agents are beginning to operate industrial energy equipment, and what they get right depends on what they are told about the plant. Established…
- arXiv cs.AIagentsTrajectory-Guided Fault Localization for Agent Skill Evolution
arXiv:2610.11858v1 Announce Type: cross Abstract: Agent skills provide reusable guidance for code agents, but incomplete or unsuitable guidance can impair task execution. To reduce the manual effort of skill refinement,…
- arXiv cs.AIagentsForms of LLM-Integrated Applications from LLM-Chats to Autonomous AI Agent System
arXiv:2610.11899v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly embedded as components in software systems, marketed under labels such as chatbot, copilot, retrieval-augmented generation,…
- arXiv cs.AIagentsCan LLMs Fix It Without Code? Toward Automated Verification of No-Code Bug Fixes
arXiv:2610.11963v1 Announce Type: cross Abstract: A no-code fix resolves an invalid bug report by directing the user to change a setting, update to a version where the problem is already fixed, or adjust their workflow.…
- arXiv cs.AIagentsAgentic-TTT: Training test-time policy for test-time training
arXiv:2610.12002v1 Announce Type: cross Abstract: Test-time training (TTT) adapts an LLM's parameters using signals derived from test inputs, and can make striking improvements in pre-specified settings such as IMO compe…
- arXiv cs.AIagentsExamining Social Attribution in LLM Reasoning: A Theory-Guided Probing Methodology
arXiv:2610.12022v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in sociotechnical systems where social attribution, the reasoning process attributing external events to the causes…
- arXiv cs.AIagentsA Closer Look at Agentic BBO: Benchmarking LLM Agents for Black-Box Optimization
arXiv:2610.12183v1 Announce Type: cross Abstract: Black-box optimization (BBO) arises in many scientific and engineering problems where objective evaluations are expensive and limited. Recent large language model (LLM) a…
- arXiv cs.AIagentsDVD: Dynamic Vector Decoding for Efficient MLLM-based Perception
arXiv:2610.12266v1 Announce Type: cross Abstract: Multimodal large language models have made remarkable progress in bridging vision and language, facilitating various perception tasks essential for human-machine interact…