AI news archive.
4,963 articles filed under Agents, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsCueKFS: Agentic Cue-Driven Keyframe Selection for Long Video Understanding
arXiv:2609.31873v1 Announce Type: cross Abstract: Keyframe selection (KFS) has long produced compact video summaries for browsing and retrieval, and representative frames for thumbnails. More recently, when conditioned o…
- arXiv cs.AIagentsCyberWorld: World Models for Sample-Efficient Autonomous Cyber Defense
arXiv:2609.31893v1 Announce Type: cross Abstract: Deep reinforcement learning has become a prominent approach to autonomous cyber defense. Existing methods are predominantly model-free and consequently require extensive…
- arXiv cs.AIagentsOverview of the TREC 2025 Million Large Language Models track
arXiv:2609.31921v1 Announce Type: cross Abstract: Agentic AI envisions ecosystems of intelligent agents collaboratively solving complex tasks with minimal human intervention. In such ecosystems, each agent possesses spec…
- arXiv cs.AIagentsVibe Analysis: Exploring LLM Adoption by Data Visualization Practitioners
arXiv:2609.31922v1 Announce Type: cross Abstract: Large language models (LLMs) are enticing in their promise to support data visualization (Vis) through faster and simpler workflows for data prep, analysis, and visualiza…
- arXiv cs.AIagentsVReAct: Verification as an Architectural Layer for LLM Agents: A V-Model Design, and a Pilot Study of Its Deterministic Core
arXiv:2609.31937v3 Announce Type: replace-cross Abstract: Large language model (LLM) agents built on the ReAct pattern concentrate four responsibilities in one model: selecting a strategy, choosing each action, formattin…
- arXiv cs.AIagentsCaptchaArena: A Large-Scale, Fine-Grained Dataset for Training Computer-Use Agents on Interactive CAPTCHAs
arXiv:2609.31957v1 Announce Type: cross Abstract: Interactive CAPTCHAs remain challenging for computer-use agents, while existing datasets face trade-offs among type coverage, interaction fidelity, and trajectory supervi…
- arXiv cs.AIagentsSilentCall: Hidden Tool-Call Backdoors in Open-Weight Agents, and How to Catch Them
arXiv:2609.32021v1 Announce Type: cross Abstract: Open-weight tool-calling agents are adopted on evidence of merit, usually benchmark scores and a record of reliable use. We show that a model publisher can train an agent…
- arXiv cs.AIagentsInteractive Distributionally Robust Multi-Agent Learning with General Function Approximation
arXiv:2609.32048v1 Announce Type: cross Abstract: Model misspecification poses a fundamental challenge in multi-agent reinforcement learning, where transition uncertainty can be amplified by strategic interactions among…
- arXiv cs.AIagentsOn Evaluating and Improving Conversational Agents in Production
arXiv:2609.32092v1 Announce Type: cross Abstract: We present a framework for evaluating and improving a large-scale, multi-agent shopping assistant in production, and report lessons from its use. Offline evaluation of su…
- arXiv cs.AIagentsOneFixer: High-Quality and Consistent One-Step Autoregressive 3DGS Refinement for Driving Scenes
arXiv:2609.32175v1 Announce Type: cross Abstract: Autoregressive video diffusion is a promising render-time fixer for 3D Gaussian Splatting (3DGS) in autonomous-driving simulation, but deployment demands high visual qual…
- arXiv cs.AIagentsAgents as Software: A Programming Languages Agenda for Agent Reliability
arXiv:2609.32198v1 Announce Type: cross Abstract: AI agents increasingly resemble software systems: they call tools, remember facts, follow policies, delegate work, and take actions with real consequences. % Yet the ``pr…
- arXiv cs.AIagentsLaMET-Agent: An Agent Framework for Large-Momentum Effective Theory Analysis
arXiv:2609.32225v1 Announce Type: cross Abstract: Large-momentum effective theory (LaMET) provides a first-principles framework for computing the $x$ dependence of light-cone parton distributions from lattice QCD. Over t…
- arXiv cs.AIagentsToward Agentic Optical Networks: A Vision of LLM Agent-Driven Autonomous Lifecycle Management
arXiv:2609.32226v1 Announce Type: cross Abstract: As optical networks continue to expand in scale, complexity, and service diversity, the implementation of automation has become essential for ensuring agility, efficiency…
- arXiv cs.AIagentsWhat Can a Leaderboard Certify? Compositional Controllability for Fair Evaluation and Training of Biomedical Literature-Review Agents
arXiv:2609.32318v1 Announce Type: cross Abstract: Leaderboards rank long-horizon agents by their final outputs. Yet a higher score alone does not establish whether two systems are comparable or which stage accounts for t…
- arXiv cs.AIagentsBlack-Box Auditing of Epistemic Reliability in Multi-Agent Debate Distillation
arXiv:2609.32361v1 Announce Type: cross Abstract: Debate distillation adapts weaker verifiers using multi-agent debate transcripts to improve their judgement in subsequent debates, but gains on monitored tasks do not est…
- arXiv cs.AIagentsMeasurement Boundaries in LLM Financial Agent Evaluation: Fixed-Tape Execution and Multi-Defect Auditing
arXiv:2609.32379v1 Announce Type: cross Abstract: What controls are needed to interpret execution performance and audit scores in LLM agent evaluations? We study two limits on these interpretations in a financial agent h…
- arXiv cs.AIagentsDashAct: A Progressive Diagnostic Benchmark for GUI Agents in Interactive Dashboard Analysis
arXiv:2609.32385v2 Announce Type: replace-cross Abstract: Interactive dashboards require users to reveal and connect evidence across stateful interactions. Although graphical user interface (GUI) agents could automate th…
- arXiv cs.AIagentsSkillDRE: Dual-Stage Red-Team Evolution of Agent Skills via Pre-Execution and Runtime Feedback
arXiv:2609.32400v1 Announce Type: cross Abstract: Agent skills package instructions, executable code, and task-specific resources into reusable artifacts that agents can improve using execution feedback. The same mechani…
- arXiv cs.AIagentsShared Worlds, Private Minds: Structured Memory for Long-Form Writing as World Creation
arXiv:2609.32401v1 Announce Type: cross Abstract: LLM agents that write long-form fiction need an explicit memory of the evolving storyworld to keep new events consistent with established facts. Such memory must keep het…
- arXiv cs.AIagentsRE-0: Verified Recursive Improvement of Embodied Code-as-Policy Agents through Local On-Policy Distillation
arXiv:2609.32416v1 Announce Type: cross Abstract: Code-as-Policy agents accomplish long-horizon embodied tasks by generating and executing code, yet continually improving them with teachers that are stronger but not glob…
- arXiv cs.AIagentsCyberClear: A Benchmark for LLM Agent Systems on APT Attack Chain Provenance
arXiv:2609.32424v1 Announce Type: cross Abstract: Large language model agents have demonstrated promising capabilities in cybersecurity tasks, yet their ability to reconstruct complete Advanced Persistent Threat attack c…
- arXiv cs.AIagentsHearsay: Can an Auditor Trust the Record a Deployed Agent Harness Writes?
arXiv:2609.32495v1 Announce Type: cross Abstract: An agent harness, the code that turns a model into an agent, writes its own record of each run, and that record is all a later reader gets when a run is disputed, investi…
- arXiv cs.AIagentsREFINE: A Resilient Evolution Framework for Intelligent Enterprise Alert Triage in Security Operations Centers
arXiv:2609.32516v1 Announce Type: cross Abstract: Security Operations Centers (SOCs) process large volumes of alerts daily. Alert triage prioritizes high-risk threats while reducing manual review of benign alerts. LLM ag…
- arXiv cs.AIagentsWhen Users Change Their Minds: Measuring and Repairing Intent Drift in LLM Agents
arXiv:2609.32520v1 Announce Type: cross Abstract: LLM agents often operate over multi-turn interactions in which user intent changes before execution. We study intent drift: the failure mode in which superseded parts of…
- arXiv cs.AIagentsDo Audio LLMs Listen Before They Act? Diagnosing Acoustic-Context Gating in Voice Agents
arXiv:2609.32536v1 Announce Type: cross Abstract: Audio language models can recognize spoken commands and invoke tools, but an agent must first decide whether the acoustic and conversational context warrants action. We i…
- arXiv cs.AIagentsRetrieved but Not Delivered: Multimodal Memory Delivery for Long-Term Agents
arXiv:2609.32590v1 Announce Type: cross Abstract: Work on memory for multimodal agents optimizes what is written, updated and retrieved. Between retrieval and the answer, however, is a stage that multimodal memory evalua…
- arXiv cs.AIagentsTrust the Brand, Lose Control: How Identity Hijacks LLM Agent Orchestration
arXiv:2609.32635v1 Announce Type: cross Abstract: LLM agents now execute tasks end to end with permission to change real systems and increasingly orchestrate subagents that differ in capability and cost. Prior work treat…
- arXiv cs.AIagentsAsynCodeBench: Benchmarking Collaboration of Asynchronous Multi-Agent Systems in Software Engineering
arXiv:2609.32662v1 Announce Type: cross Abstract: Multi-agent coding has emerged as an increasingly active direction in software engineering, where complex development tasks are decomposed across multiple specialized age…
- arXiv cs.AIagentsThe GUI Is Not the State: Diagnosing State Aliasing in GUI World Models
arXiv:2609.32679v1 Announce Type: cross Abstract: GUI World Models (GUI-WMs) are increasingly used to predict future states for agent planning and simulation, yet most existing formulations condition only on the current…
- arXiv cs.AIagentsSelf-Evolving Multi-Agent Symbolic Discovery for Financial Fundamental Analysis
arXiv:2609.32746v1 Announce Type: cross Abstract: While symbolic regression (SR) has been successfully used in science to discover new equations, its use in financial valuation is hindered by several limitations. Whereas…
- arXiv cs.AIagentsPolyTopoBench: A Benchmark for Complex Vector Polygon Generation from Remote Sensing Imagery
arXiv:2609.32856v1 Announce Type: cross Abstract: Vector polygon generation converts visual inputs, e.g., remote sensing (RS) images, into vectorized polygonal geometries, supporting applications such as autonomous drivi…
- arXiv cs.AIagentsRoboFoundry: System-as-Policy Evolution for Self-Learning Embodied Agents
arXiv:2609.32862v1 Announce Type: cross Abstract: A foundation model should not act in isolation as an embodied agent. Yet, existing methods often optimize individual components of the agent stack, such as memory, contex…
- arXiv cs.AIagentsASCEND: Personal AI Agents for Autonomous Scientific Computing Across HPC Clusters and GPU Workstations
arXiv:2609.32868v4 Announce Type: replace-cross Abstract: Traditional scientific computing requires researchers to translate intent into environment configuration, resource requests, and executable jobs, then diagnose fa…
- arXiv cs.AIagentsAgentTell: Behavioural Side-Channel Leakage in Browser-Use Agents
arXiv:2609.32915v1 Announce Type: cross Abstract: Browser-use agents often carry information in their context as they move between websites. While it may be necessary for task completion, it also creates a privacy risk,…
- arXiv cs.AIagentsVision-Language Agents for Active Perception in Optics Laboratories
arXiv:2609.32918v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly being used in scientific workflows, but their ability as agents to directly control laboratory experiments from visual feed…
- arXiv cs.AIagentsEnvironmental Impact of Generative and Agentic AI: An in-Depth Analysis and Green Solutions
arXiv:2609.32960v1 Announce Type: cross Abstract: The proliferation of generative and agentic artificial intelligence (AI) systems has introduced computational demands whose environmental consequences are substantial yet…
- arXiv cs.AIagentsBeyond Token Savings: A Systematic Study of Context Compression in LLM Agents
arXiv:2609.32961v1 Announce Type: cross Abstract: As LLM agents tackle longer tasks, they increasingly compress growing histories of reasoning, actions, and tool outputs. Compression can reduce token use, but it also cha…
- arXiv cs.AIagentsParallelPilot: Supporting Coordination and Monitoring in Parallel AI Coding
arXiv:2609.33113v1 Announce Type: cross Abstract: As coding assistants become increasingly autonomous, developers run multiple sessions in parallel, shifting the challenge from code generation alone to coordinating and m…
- arXiv cs.AIagentsECG-Scroll: A Long-Horizon, Streaming Benchmark and Agent Environment for Interpretation of Ambulatory Electrocardiograms
arXiv:2609.33117v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) can now interpret a standard ten-second, twelve-lead electrocardiogram (ECG) with clinically grounded, reward-verified reasoning.…
- arXiv cs.AIagentsWhat Does a Skill Actually Do? Estimands and Evaluation Validity for Tool and Skill Use in LLM Agents: A Critical Review
arXiv:2609.33153v2 Announce Type: replace-cross Abstract: Reported improvements from tools and reusable skills in large language model agents refer to different comparisons. This critical narrative review examines what t…
- arXiv cs.AIagentsBeyond Tasks: A Vision for Reproducing an Animal-like Behavioral Substrate Using Modern Robot Learning Techniques
arXiv:2609.33165v1 Announce Type: cross Abstract: Recent advances in robot learning have produced increasingly capable embodied agents. Yet comparatively less attention has been given to a more basic form of competence t…
- arXiv cs.AIagentsWhich Self-Improvements Should We Trust? Reliable Self-Improvement When Agents Reuse Their Benchmarks
arXiv:2609.33180v2 Announce Type: replace-cross Abstract: As recursive self-improvement (RSI) rapidly advances, reliable evaluation becomes critical for guiding adaptive search. RSI typically relies on finite evaluation…
- arXiv cs.AIagentsTAO-DA: Towards Autonomous Operation--A Dual-Arm Vision-Language-Action Model for Coordinated Manipulation
arXiv:2609.33197v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models provide a unified framework for grounding high-level semantic information into low-level robot actions, enabling scalable robotic mani…
- arXiv cs.AIagentsInspire: Benchmarking Scientific Literature Search for Open Research Problems
arXiv:2609.33233v1 Announce Type: cross Abstract: Scientific literature search often begins with an open research problem rather than a known target paper or a fixed candidate set. We introduce INSPIRE, a benchmark for e…
- arXiv cs.AIagentsVehDyn: A Driving World Model Benchmark for Vehicle Dynamics
arXiv:2609.33264v1 Announce Type: cross Abstract: Video world models are emerging as data engines, action planners, and generative simulators for autonomous driving, but existing benchmarks primarily assess visual fideli…
- arXiv cs.AIagentsAquaWAM: A Dynamics-aware World Action Model for Underwater Embodied Agents
arXiv:2609.33299v2 Announce Type: replace-cross Abstract: World Action Models (WAMs) are becoming increasingly important and useful for embodied intelligence, as they enable robots to anticipate the consequences of candi…
- arXiv cs.AIagentsRobust Hierarchical Structures for Agentic Document Analysis
arXiv:2609.33322v1 Announce Type: cross Abstract: Large Language Models (LLMs) enable us to better understand text documents, including PDFs and Word documents. However, LLMs, as well as more modern LLM agents, i.e., tho…
- arXiv cs.AIagentsDoes Learning to Predict the World Help Agents Act? Auditing World-Model Post-Training
arXiv:2609.33335v1 Announce Type: cross Abstract: Predicting how an environment will change before acting is a natural route to better decision making for agents. Recent post-training methods therefore require agents to…
- arXiv cs.AIagentsAPI Secrets Should Never Become Tokens in the LLM's Vocabulary: A Threat Analysis of API Credential Handling in LLM Agent Systems and an Empirical Evaluation of a Vault-Mediated Execution Boundary
arXiv:2609.33371v1 Announce Type: cross Abstract: Tool-using large language model (LLM) agents turn credential hygiene from a storage problem into an execution-security problem. A key pasted into a prompt, or embedded in…
- arXiv cs.AIagentsRecursive Harness Distillation across Agents for Robot Manipulation
arXiv:2609.33378v1 Announce Type: cross Abstract: A central goal in robotics is to enable manipulation across changing tasks and environments. Vision-language-action (VLA) models provide broad manipulation capabilities b…