AI news archive.
4,965 articles filed under Agents, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsNot All AI Agents Are Equal: Characterizing Resource and Performance Dynamics
arXiv:2609.19947v2 Announce Type: replace Abstract: LLM-based AI agents process user requests through iterative reasoning and tool execution, often involving the invocation of remote LLM APIs with local tool containers.…
- arXiv cs.AIagentsNeuro-Symbolic Agentic AI for Networked Low-Altitude UAVs
arXiv:2609.19961v1 Announce Type: new Abstract: Networked low-altitude unmanned aerial vehicles (UAVs) need reliable and adaptive decision-making capabilities to operate under uncertain observations, dynamic environments…
- arXiv cs.AIagentsA Proposal for an Agentic AI Architecture to Support Multi-Domain Decision-Making in the Brazilian Armed Forces
arXiv:2609.20080v1 Announce Type: new Abstract: The growing complexity of multi-domain operational environments (land, aerospace, naval, cyber, and electromagnetic spectrum) has increased the volume and velocity of data…
- arXiv cs.AIagentsUnifiedPlayers: Enhance Tool-Integrated Reasoning in Agentic Reinforcement Learning
arXiv:2609.20089v1 Announce Type: new Abstract: Self-evolving methods reduce the need for human-annotated trajectories by allowing tool-using agents to generate their own training data. Yet existing methods typically sep…
- arXiv cs.AIagentsMTVA-Bench: Evaluating the Language Model Inside Cascaded Voice Agents
arXiv:2609.20152v1 Announce Type: new Abstract: Generally, most voice agents are cascaded systems, i.e., an ASR model transcribes the caller's audio, a language model reads the transcript and decides what to say and whic…
- arXiv cs.AIagentsWhen AI Agents Commit: Cognitive Serializability Across Data, Evidence, Policy, and Authority
arXiv:2609.20261v1 Announce Type: new Abstract: Autonomous agents derive concrete mutations from database reads, retrieved evidence, policy, beliefs, and delegated authority. Those inputs may change while reasoning is in…
- arXiv cs.AIagentsAgentPProf: Semantic Profiler for Long Horizon AI Agents
arXiv:2609.20301v1 Announce Type: new Abstract: AI agents increasingly orchestrate long-running activities with users, tools, and system resources for days and weeks. To improve agent quality, safety, and cost efficiency…
- arXiv cs.AIagentsThe Organization of Inference: Information, Resource Constraints, and AI Production
arXiv:2609.20449v1 Announce Type: new Abstract: The economic value of inference depends on how capacity and task information are distributed across stages of AI production. We study these organizational margins using con…
- arXiv cs.AIagentsHow Do Agent Harnesses Create Value? Planning Information and Release Control in Stateful LLM Agents
arXiv:2609.20474v1 Announce Type: new Abstract: Agent harnesses supply planning guidance, organize execution, and check completion. We study how these components affect success, erroneous acceptance, and cost in two Reta…
- arXiv cs.AIagentsSoL-Pi: Recursively Scaling Auto-Research Loops for Efficient Agent Harness
arXiv:2609.20519v1 Announce Type: new Abstract: As coding agents move from supervised code completion to unattended, around-the-clock exploration, their work expands from isolated predictions into long trajectories of re…
- arXiv cs.AIagentsDeep Noir: Autonomous Steering Discovery via Architectural Chronometry in Transformer Models
arXiv:2609.20722v1 Announce Type: new Abstract: Activation steering modifies LLM behavior at inference time, but identifying where and how strongly to steer remains manual. We introduce Deep Noir, a framework that uses L…
- arXiv cs.AIagentsRAFT: A Stateful Retrieval-Augmented Framework for Troubleshooting Agents
arXiv:2609.20754v1 Announce Type: new Abstract: Effective troubleshooting agents in enterprise customer support depend on retrieving actionable guidance from similar historical cases, yet existing retrieval-augmented gen…
- arXiv cs.AIagentsAn Empirical Study of Harness Design for Coding Agents
arXiv:2609.20804v1 Announce Type: new Abstract: Coding harnesses shape how autonomous coding agents translate model capabilities into long-horizon software-engineering performance, yet existing work typically evaluates h…
- arXiv cs.AIagentsPAPC: Platform Mediation for Privacy-Propagation Externalities in AI-Mediated Workflows
arXiv:2609.19226v1 Announce Type: cross Abstract: AI-mediated platforms coordinate work through LLM agents acting for different principals. In these workflows, privacy loss can be created before a final answer appears: a…
- arXiv cs.AIagentsThe AR Fairness Metamodel: A Structured Framework for Fairness Measures
arXiv:2609.19234v1 Announce Type: cross Abstract: This paper presents the AR fairness metamodel, a framework designed to represent, analyze, and compare different fairness scenarios. The metamodel considers key elements,…
- arXiv cs.AIagentsKinematics-Grounded Agentic AI for Robotic Additive Manufacturing Process Planning
arXiv:2609.19347v1 Announce Type: cross Abstract: Robotic additive manufacturing (AM) extends material-extrusion printing beyond gantry kinematics but makes process planning robot-dependent. A slicer-generated plan that…
- arXiv cs.AIagentsFrom Rollout to Reset: A Graph-Based Harness for Autonomous Long-Horizon Manipulation Evaluation
arXiv:2609.19413v1 Announce Type: cross Abstract: Robot manipulation policies are improving quickly, and real-robot evaluation remains the standard evidence for that progress. It still relies on a human to reset the scen…
- arXiv cs.AIagentsEfficiently Linking Unstructured Data for Multi-step Reasoning
arXiv:2609.19491v1 Announce Type: cross Abstract: Modern LLMs and AI agents increasingly support data engineering workflows that integrate evidence from unstructured sources. Such pipelines typically do data retrieval, i…
- arXiv cs.AIagentsFor Your Eyes Only: Evaluating Coordination Between Isolated Language Model Instances
arXiv:2609.19504v1 Announce Type: cross Abstract: As model-generated content is increasingly consumed by other model instances in automated workflows, a practically important question arises: can a model embed a signal i…
- arXiv cs.AIagentsAURORA: A Natural Language-Driven Agentic Framework for Understanding, Reasoning, and Orchestrating Reliable Air-Ground Co-Simulation
arXiv:2609.19527v1 Announce Type: cross Abstract: Air-ground transportation research increasingly relies on co-simulation, yet constructing scenarios remains labor-intensive and difficult to validate. More importantly, a…
- arXiv cs.AIagentsLarge Language Model Agents for Evidence Based Genetic Disease Severity Classification
arXiv:2609.19569v2 Announce Type: replace-cross Abstract: Disease severity classification for genetic conditions is subjective and labor-intensive, creating bottlenecks in genomic screening, where commercial panels vary…
- arXiv cs.AIagentsRed-Teaming Auto Mode: Improving Blocking Classifiers Against Malign Coding Agents
arXiv:2609.19587v2 Announce Type: replace-cross Abstract: To keep coding agents from going off the rails, production systems now review each proposed action with a blocking monitor that can reject it before it runs (Auto…
- arXiv cs.AIagentsDeltaSelect: Affordable A/B Testing for Coding Agents
arXiv:2609.19607v1 Announce Type: cross Abstract: Coding-agent benchmarks are built for broad and comprehensive comparisons, not frequent development decisions. Individual runs vary, full suites are expensive, and the be…
- arXiv cs.AIagentsDataCanvas-EDU: An Agentic Framework for Instructor-Guided Synthetic Data Generation in Business Analytics Education
arXiv:2609.19617v2 Announce Type: replace-cross Abstract: Business analytics education requires diverse datasets to support different learning objectives, student backgrounds, and analytical tasks. Real-world data can be…
- arXiv cs.AIagentsSelf-Evolving Search Index
arXiv:2609.19656v1 Announce Type: cross Abstract: Information retrieval is increasingly important as LLM agents tackle complex tasks involving diverse information needs. Because retrieval relies on an index that represen…
- arXiv cs.AIagentsTrading Agents or Market Crashers? Dissecting Robustness and Security Failures in Academic Financial LLM Trading Schemes
arXiv:2609.19705v3 Announce Type: replace-cross Abstract: Large language model (LLM) agents already trade real capital, and builders copy a few published designs that share models and news feeds, so one shock reaches man…
- arXiv cs.AIagentsLong-horizon autoformalization of a core theorem underlying MIP* = RE
arXiv:2609.19814v3 Announce Type: replace-cross Abstract: Landmark mathematical formalizations have taken specialist teams years to complete. We present FormalFlow, a system that coordinates AI proving agents under human…
- arXiv cs.AIagentsClashBench: Conflicts Leading Agents to Seize and Harm
arXiv:2609.19892v1 Announce Type: cross Abstract: As agent systems become more widely used, multiple agent sessions increasingly run alongside pre-existing user tasks in the same environment, sharing resources with limit…
- arXiv cs.AIagentsLearning and Transferring Closed-Loop Robot Software
arXiv:2609.19906v3 Announce Type: replace-cross Abstract: Closed-loop robot policies require observation processing, state management, and situation-dependent branching, making them costly to design and tune manually. Al…
- arXiv cs.AIagentsThe Missing Complement: State-Conditioned Minimal Sufficient Evidence for Coding Agents
arXiv:2609.20050v2 Announce Type: replace-cross Abstract: Retrieval assembles repository context by ranking passages for relevance to the current query. A coding agent halfway through an issue has already read much of wh…
- arXiv cs.AIagentsRobust Workflow Generation via Adversarial Learning for Audio Deepfake Detection
arXiv:2609.20063v1 Announce Type: cross Abstract: The rapid advancement of speech synthesis and voice conversion technologies has made audio deepfakes increasingly realistic, posing serious security risks in practical ap…
- arXiv cs.AIagentsA Scalable Trust Discovery Architecture for the Internet of Agents
arXiv:2609.20095v1 Announce Type: cross Abstract: The Internet of Agents is expected to enable large numbers of autonomous agents to discover, verify, and collaborate with each other across heterogeneous platforms. Howev…
- arXiv cs.AIagentsDesigning Against Deskilling: Metacognitive Feedback Reduces Cognitive Offloading to LLM Assistants
arXiv:2609.20143v1 Announce Type: cross Abstract: Cognitive offloading to AI can reduce opportunities to practice skills, creating risks of deskilling. However, it remains unclear how to prevent deskilling without restri…
- arXiv cs.AIagentsLLM-Guided Transformation of Non-Critical Driving Scenes into Safety-Critical Scenarios Using Augmented Reality
arXiv:2609.20318v1 Announce Type: cross Abstract: Testing Autonomous Driving Systems (ADS) requires realistic safety-critical scenarios, but collecting such data from real-world driving is costly and unsafe. This paper p…
- arXiv cs.AIagentsSTR-Agent: An LLM-Driven Agent for QoS-Aware Routing in LEO Satellite Networks
arXiv:2609.20347v1 Announce Type: cross Abstract: LEO satellite networks feature dynamic topologies, time-varying links, and diverse service requirements, which make conventional routing schemes difficult to support fine…
- arXiv cs.AIagentsModel-Agnostic and Language-Agnostic Voice Pipeline Improvement for the Agriculture Domain
arXiv:2609.20504v1 Announce Type: cross Abstract: FarmerChat is Digital Green's AI-powered agricultural advisory assistant for smallholder farmers, who access it in their own language through text, voice, or photographs.…
- arXiv cs.AIagentsMitigating Retaliatory Algorithmic Collusion in Repeated Games
arXiv:2609.20548v1 Announce Type: cross Abstract: Reinforcement learning agents trained to maximize their own reward in repeated interactions can converge to supra-competitive outcomes resembling explicit collusion, with…
- arXiv cs.AIagentsA Simulation Platform for AUV Fault Recovery: Exploring LLM-Based Diagnostic Strategies
arXiv:2609.20620v1 Announce Type: cross Abstract: Autonomous underwater vehicles (AUVs) operating beyond reliable communications must recover from failures without human intervention. We investigate an architecture in wh…
- arXiv cs.AIagentsChronicle: Cut-Point Replay for Regression Testing of LLM Agents
arXiv:2609.20625v1 Announce Type: cross Abstract: Large language model responses are non-deterministic, so failures in LLM agents are hard to reproduce: a failure depends on inference that is not bitwise reproducible, on…
- arXiv cs.AIagentsDon't Mask the Environment: Observation Supervision Changes How Agents Explore Under RL
arXiv:2609.20715v1 Announce Type: cross Abstract: Agent trajectories record what an agent does and what happens next. Yet standard supervised fine-tuning (SFT) applies loss only to agent-authored action tokens, using env…
- arXiv cs.AIagentsPrediction-Powered Smoothing and Validation for Disaggregated AI Evaluation
arXiv:2609.20758v1 Announce Type: cross Abstract: Evaluating an AI system requires disaggregated assessment, as performance varies across domains such as benchmark task types or conversation types in deployed agents. Exh…
- arXiv cs.AIagentsSemantic Action Graph: A Shared Representation for Agent Grounding and Human Interpretation of Sports Highlights
arXiv:2609.20768v2 Announce Type: replace-cross Abstract: Generative agents are increasingly used to select and narrate video highlights, but they typically operate over unstructured or frame-level representations. Their…
- arXiv cs.AIagentsRetireOPD: Self-Retiring On-Policy Distillation for Agentic Reinforcement Learning
arXiv:2609.20784v2 Announce Type: replace-cross Abstract: Multi-turn agents trained with reinforcement learning (RL) receive a single scalar reward per trajectory, which motivates self on-policy distillation (OPD) to sup…
- arXiv cs.AIagentsQuantifying Overclaiming Propensity in Frontier LLM Agents
arXiv:2609.20812v3 Announce Type: replace-cross Abstract: Frontier coding agents are increasingly trusted to work autonomously for long periods of time, yet what they actually did is often hard to tell from their final r…
- arXiv cs.AIagentsCoding Agents with Harness for Safe Robot Control
arXiv:2609.20822v2 Announce Type: replace-cross Abstract: Coding agents have emerged as a promising paradigm for robot manipulation: a language model writes the robot controller as a program, and agents built in this way…
- arXiv cs.AIagentsArchitectural Design, Not Only Model Intelligence, Governs Multi-Agent LLM Performance
arXiv:2602.03128v2 Announce Type: replace Abstract: Multi-agent LLM frameworks are data-intensive systems that govern how agents orchestrate tasks, manage state, and coordinate decisions. These architectural choices cont…
- arXiv cs.AIagentsReinforcing the World's Edge: A Continual Learning Problem in the Multi-Agent-World Boundary
arXiv:2603.06813v3 Announce Type: replace Abstract: Ordinary decentralized multi-agent reinforcement learning presents each focal agent with a continual learning problem: peer updates change its induced rewards and dynam…
- arXiv cs.AIagentsSemantic Feature Analysis: Improving Agents Without Searching Over Rollouts
arXiv:2604.10513v2 Announce Type: replace Abstract: Ambiguity is an inherent property of natural-language agent specifications. When a system prompt leaves behaviour underdetermined, identical inputs follow divergent exe…
- arXiv cs.AIagentsFaithful, Not Corrective: Model Capability Governs Message-Format Effects in Multi-Hop Agent Relays
arXiv:2607.09678v2 Announce Type: replace Abstract: When LLM agents hand information to one another, does the message format matter? Two literatures disagree: format-optimization work reports that structured messages cut…
- arXiv cs.AIagentsWhen Self-Evolution Backfires: Pre-Commit Gating against Skill Contamination in LLM Agents
arXiv:2608.05810v2 Announce Type: replace Abstract: Self-evolving agents accumulate capability by distilling reusable skills from their execution trajectories, but we find this process is not monotonic: past a critical p…