AI news archive.
4,965 articles filed under Agents, newest first, from the outlets listed on the sources page.
- OpenAI NewsagentsRadisson Hotel Group brings hotel discovery into ChatGPT
Radisson partnered with Accenture to build a ChatGPT plugin using OpenAI technology, helping travelers find, compare, and book hotels while planning their trips.
- arXiv cs.AIagentsGAMEGO: Training Game-Dev Agents with Synthetic Trajectories Anchored in Real-World Assets
arXiv:2610.06910v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have demonstrated remarkable capabilities in web front-end execution, with browser-based game generation emerging as a parti…
- arXiv cs.AIagentsA Governed Agent Architecture for Natural-Language Dashboard Generation over Enterprise DataBrain
arXiv:2610.06914v2 Announce Type: replace Abstract: We present a DataBrain-specific prototype that turns natural-language analytic requests into inspectable dashboards. An installable Codex plugin and standalone Agent Ru…
- arXiv cs.AIagentsRadOnc-Agent: An Integrated Framework for AI Workflows Across the Radiotherapy Care Pathway
arXiv:2610.06923v2 Announce Type: replace Abstract: Artificial intelligence has advanced radiotherapy tasks, but these capabilities remain fragmented across the care pathway. Here we present RadOnc-Agent, an integrated f…
- arXiv cs.AIagentsPrinciples that Guide, Actions that Inform: Agent Evolution via Knowledge Abstraction
arXiv:2610.06964v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated strong capabilities in interactive environments, yet their ability to continually evolve from experience remains limited…
- arXiv cs.AIagentsAegisFlow: A Multi-Agent Agentic AI Framework for Autonomous Remediation and Self-Healing in Fragile Data Ecosystems
arXiv:2610.06971v1 Announce Type: new Abstract: Traditional data pipelines are notoriously brittle, often failing due to upstream schema drift, API contract changes, or website DOM modifications. Present observability to…
- arXiv cs.AIagentsEPOCH: Reliable Discovery through Evidence-Governed Search
arXiv:2610.06986v1 Announce Type: new Abstract: AI research agents are increasingly used to search over programs, mathematical constructions, and proofs. However, existing systems typically optimize evaluator feedback wi…
- arXiv cs.AIagentsTopology-Consistent Task Planning over Cellular Workflow Complexes for LLM-based Agents
arXiv:2610.07004v1 Announce Type: new Abstract: Task planning for LLM agents requires workflows that satisfy both user intent and complex sub-task dependencies. While existing planners work well for sequential or directe…
- arXiv cs.AIagentsCuratorMAS: Automating Dataset Curation via Multi-Agent Orchestration
arXiv:2610.07075v1 Announce Type: new Abstract: High-quality datasets are essential for reliable machine learning, but dataset curation remains costly and hard to generalize across domains. Existing methods typically rel…
- arXiv cs.AIagentsWhen to Remember, When to Abstain: Category-Conditioned Retention for Reliable Agent Memory
arXiv:2610.07100v1 Announce Type: new Abstract: Persistent agent memory is only as reliable as its retention decision: an assertion weakly supported by its source can be stored and later reused as established fact. We st…
- arXiv cs.AIagentsAMBER: Training Long-Horizon Web Agents through Append-Only Memory
arXiv:2610.07118v1 Announce Type: new Abstract: Modern language-model agents increasingly interact with external environments over long-horizon, multi-step trajectories, where the accumulated interaction history can quic…
- arXiv cs.AIagentsIs this machine playing?
arXiv:2610.07130v1 Announce Type: new Abstract: We placed a modern AI coding assistant in an unintended role: as the mind of a body on an unknown digital island. With only a minimal instruction mentioning no specific tas…
- arXiv cs.AIagentsCan Semantic Geometry Teach an AI Judgement?
arXiv:2610.07249v1 Announce Type: new Abstract: How can an AI agent determine what rules to follow? One rule permits an action. Another imposes a condition, exception, or conflicting obligation. Deterministic systems can…
- arXiv cs.AIagentsInternalizing Agent Experience into Diffusion Model Weights via On-Policy Context Distillation
arXiv:2610.07250v1 Announce Type: new Abstract: Wrapping an image generation model in an agentic harness can effectively boost Text-to-Image task performance: the harness can leverage memory, skills, workflow orchestrati…
- arXiv cs.AIagentsMemMux: Runtime Verification and Honest Resource Attribution for Fleets of Parallel Coding Agents
arXiv:2610.07257v2 Announce Type: replace Abstract: Developers increasingly run a fleet of coding agents side by side on one workstation. Terminal multiplexers like tmux and a new generation of agent managers were built…
- arXiv cs.AIagentsVerifying Coordination in Parallel Coding Agents: NP-Bench and a Scheduling Planner
arXiv:2610.07261v1 Announce Type: new Abstract: A team of coding agents can look fine agent by agent yet fail as a team: each passes its own tests while the merged result is broken, and single-agent evaluation never catc…
- arXiv cs.AIagentsA Trust Layer for Agent Evaluation
arXiv:2610.07274v1 Announce Type: new Abstract: Deterministic benchmark scores show that an agent received credit, but not whether that credit was earned, reported honestly, or would hold on a second run. We introduce a…
- arXiv cs.AIagentsThe Right Memory in the Wrong Context: Verifying Retrieval Admissibility in Long-Term Agent Memory
arXiv:2610.07309v1 Announce Type: new Abstract: Long-term-memory agents can retrieve relevant information that is inadmissible for the current request because it belongs to another principal, violates policy, or reflects…
- arXiv cs.AIagentsUnderstanding and Mitigating Inference-Time Overreliance Using Agentic Memory
arXiv:2610.07311v1 Announce Type: new Abstract: Agentic memory allows LLM agents to reuse past experience, yet retrieved memories can also distort inference even when they are benign, correctly stored, and appropriately…
- arXiv cs.AIagentsEvaluate the Stack, Not the Layer: Do Deterministic and LLM Gates for Agent Actions Fail Independently?
arXiv:2610.07359v2 Announce Type: replace Abstract: Runtime gates for agent tool calls are stacked on the assumption that their errors multiply. We test it on 1,119 labelled agent actions from three corpora, without an a…
- arXiv cs.AIagentsMemCo: Memory-Centric Collaboration for Generalizing LLM Agents to Unseen Environments
arXiv:2610.07376v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate in interactive environments, where they need to make sequential decisions through observation, action, and feedback.…
- arXiv cs.AIagentsAuditable Claims about AI Agents
arXiv:2610.07459v1 Announce Type: new Abstract: Organizations make claims about their AI agents: a person approves every external email, every action is logged, an evaluation shows the agent is safe to deploy. Article 12…
- arXiv cs.AIagentsPsyCIDRA: A Dual-Agent Framework for Psychiatric Interviewing and Diagnostic Reasoning
arXiv:2610.07473v1 Announce Type: new Abstract: Large language models show promise in clinical reasoning, but psychiatric interviewing requires guiding an evolving conversation. Their ability to carry out this interactiv…
- arXiv cs.AIagentsOn Open-Ended Information Seeking for Information Elicitation Agents
arXiv:2610.07509v1 Announce Type: new Abstract: Information elicitation is an open-ended information-seeking problem in which an interaction can unfold in many potentially valuable directions, requiring an elicitor to co…
- arXiv cs.AIagentsGrounding What Shapes the Plan: Rethinking Groundedness for Physical Intelligence in Autonomous Driving
arXiv:2610.07521v1 Announce Type: new Abstract: Driving models increasingly ground reasoning in causal relations, spatial structure, perceptual evidence, and predicted futures. These advances make reasoning more faithful…
- arXiv cs.AIagentsDecoupled Multi-Agent Orchestration
arXiv:2610.07556v2 Announce Type: replace Abstract: Learned orchestration can automatically construct effective language-model multi-agent systems, but existing approaches couple planning to fixed worker pools and train…
- arXiv cs.AIagentsUnanimously Wrong: Certified Abstention from How Medical LLM Consensus Forms
arXiv:2610.07570v1 Announce Type: new Abstract: In clinical practice, agreement among independent experts is treated as evidence of reliability, and multi-round consensus has become a core mechanism of agentic medical qu…
- arXiv cs.AIagentsCooperating with Future Collaborators: Multi-Agent RL under Staggered Participation
arXiv:2610.07578v1 Announce Type: new Abstract: In cooperative Multi-Agent Reinforcement Learning (MARL), agents are often trained under concurrent participation, while in many tasks some agents act earlier and leave tas…
- arXiv cs.AIagentsPersonal-Agent Mediated Recommendation with Cross-Platform User History
arXiv:2610.07588v1 Announce Type: new Abstract: Modern recommendation is shifting from platform-centric personalization toward user-governed personalization, where a personal LLM agent can act on the user's behalf across…
- arXiv cs.AIagentsBioStudyBench: Evaluating Agents on Post-Cutoff Biomedical Studies
arXiv:2610.07614v1 Announce Type: new Abstract: We evaluate whether AI agents can match the reported findings of published biomedical studies using public data. Existing evaluations do not consistently separate analysis…
- arXiv cs.AIagentsTowards the Automatic Synthesis of Interpretable Chess Tactics
arXiv:2610.07640v1 Announce Type: new Abstract: State-of-the-art reinforcement learning agents are capable of outperforming human experts at games like chess, Go and StarCraft II. These agents do not simply take advantag…
- arXiv cs.AIagentsWhere Rules End and Judges Begin: Measuring the Judgment Boundary in Multi-Agent Systems Security
arXiv:2610.07657v2 Announce Type: replace Abstract: LLM-based multi-agent systems (MAS) engage tools, share memory, and delegate tasks, often encountering adversarial content. Current defenses for MAS are typically evalu…
- arXiv cs.AIagentsEIO-Agents: The Missing Semantic Layer for AI Agent Evaluation
arXiv:2610.07675v1 Announce Type: new Abstract: AI agents are entering production in increasingly consequential environments without a shared semantic standard for what their evaluations actually mean. Scores, traces, ju…
- arXiv cs.AIagentsAgentMemGate: Addressing Speculation Contamination in Conversational Assistant Memory
arXiv:2610.07707v1 Announce Type: new Abstract: Conversational AI assistants with long-term memory extract facts from user messages into a store consulted in later conversations. A stated plan can enter that store as fac…
- arXiv cs.AIagentsPERSIST: Who-What-When Memory Across Sessions for Full-Duplex Spoken Dialogue
arXiv:2610.07725v1 Announce Type: new Abstract: Modern voice assistants may be shared by multiple users and should be able to answer questions about earlier conversations such as "When did I originally plan to leave?" or…
- arXiv cs.AIagentsHow Well Do LLMs Reason with Noisy Evidence? An Active Visual Reasoning Benchmark
arXiv:2610.07751v1 Announce Type: new Abstract: Real-world reasoning rarely reduces to static question answering: agents must actively gather information from tools and sensors that are often noisy and unreliable. Yet mo…
- arXiv cs.AIagentsST-Bench: A Spatial-Temporal Benchmark for Multi-Agent System Generation on Scientific Research Tasks
arXiv:2610.07763v1 Announce Type: new Abstract: The rapid progress of LLM-based multi-agent systems (MAS) has shown that they largely outperform single agents on coding, math, and QA tasks, where executable tests provide…
- arXiv cs.AIagentsQuantization Effects on Tool-Failure Recovery Vary Across Prompts and Evaluation Designs
arXiv:2610.07781v1 Announce Type: new Abstract: Post-training quantization reduces the cost of deploying language-model agents, but its effect on recovery from temporary tool failures can depend on how recovery is evalua…
- arXiv cs.AIagentsPersistent Memory in Multi-Agent LLM Inference: What It Costs, What It Buys, and When You Can Tell
arXiv:2610.07782v1 Announce Type: new Abstract: Decomposing long-context inference across cooperating agents bounds the active KV cache per call rather than total evidence, which matters when KV-cache memory binds. Many…
- arXiv cs.AIagentsAttacca: Goal-Directed Control under State Continuity for Long-Horizon Embodied Agents
arXiv:2610.07785v1 Announce Type: new Abstract: A central capability of embodied agents is to accomplish complex objectives through sequences of interdependent tasks. Yet existing visual goal-conditioned policies underly…
- arXiv cs.AIagentsOOPMAS: Object-Oriented Multi-Agent Systems for Query-Level Workflow Generation
arXiv:2610.07787v1 Announce Type: new Abstract: Multi-agent systems (MAS) powered by large language models have shown strong performance across code generation, mathematical reasoning, and question answering. However, ex…
- arXiv cs.AIagentsDo I Need the Cloud? Uncertainty-Aware Step-Level Handoff for Small Language Model Agents
arXiv:2610.07816v1 Announce Type: new Abstract: Small language models (SLMs) are attractive as local agent controllers because they reduce remote inference, latency, and deployment footprint, yet structured tool errors c…
- arXiv cs.AIagentsAgentic Semantic Sensing for Resource-Adaptive AI-RAN
arXiv:2610.07829v1 Announce Type: new Abstract: Semantic sensing (SemS) acquires task-relevant information rather than reconstructing complete physical information. Existing SemS formulations typically operate open loop:…
- arXiv cs.AIagentsDHCG: Dynamic Construction of Hierarchical Collaboration Graphs for LLM-Based Multi-Agent Reasoning
arXiv:2610.07835v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) have demonstrated strong capabilities in solving complex problems across diverse domains. Recently, the dynamic orchestration of agent s…
- arXiv cs.AIagentsRA-MoWE: Workflow-Affinity Embeddings for Query Clustering and Agentic Workflow Generation
arXiv:2610.07851v1 Announce Type: new Abstract: Agentic workflows enable large language models (LLMs) to solve complex tasks by coordinating reasoning, tool use, and verification. However, a workflow optimized for an ent…
- arXiv cs.AIagentsWorkflowOps: Learning Agent Collaboration Priors for Multi-Agent Workflow Orchestration
arXiv:2610.07860v1 Announce Type: new Abstract: Multi-agent systems are increasingly deployed for complex knowledge work, yet their orchestration layers remain largely memoryless: each new task is decomposed, assigned, a…
- arXiv cs.AIagentsSelf-Referenced Social Preferences: Cooperation without Observing Others Rewards
arXiv:2610.07881v2 Announce Type: replace Abstract: Social preferences can promote cooperation in multi-agent reinforcement learning, but existing approaches often require agents to observe the rewards of their peers. In…
- arXiv cs.AIagentsShanLiangRen: A Nutrition Agent for Personalized Daily Meal Planning
arXiv:2610.07886v1 Announce Type: new Abstract: Dietary nutrition planning plays an important role in chronic disease management and maintaining a healthy body. In applications, it must simultaneously satisfy personalize…
- arXiv cs.AIagentsSIGMA: Self-Improving Alignment Generalization from a Model Spec
arXiv:2610.07935v1 Announce Type: new Abstract: LLM agents are increasingly capable of executing complex tasks and of recursively improving themselves on easy-to-verify objectives such as software engineering and mathema…
- arXiv cs.AIagentsConfidence Reasoning Graphs: Structured Confidence Estimation for LLM Agents
arXiv:2610.07948v1 Announce Type: new Abstract: When using an LLM agent in a consequential domain, making an informed decision about whether to trust its output or intervene requires calibrated confidence in the agent's…