AI news archive.
4,957 articles filed under Agents, newest first, from the outlets listed on the sources page.
- SiliconANGLE AIagentsWith Agentic Studio, LinearB provides the critical context needed to accelerate software delivery
Application development intelligence startup LinearB Inc. said today it’s trying to ease the growing congestion in organization’s software delivery pipelines that has arisen with the widespread adoption of artificial int…
- MIT Technology Review AIagentsStop counting tokens, start counting what ships
When a developer gives an AI agent a coding task, the agent does more than answer once. It plans, generates code, runs tests, and repeats the process to correct errors. A single task can use 10 to 50 times more tokens th…
- MIT Technology Review AIagentsThe agentic web is here
In 2001, a decade after he invented the World Wide Web, Tim Berners-Lee articulated a new vision. Together with two colleagues, he published an article in the magazine Scientific American in which he outlined what he cal…
- SiliconANGLE AIagentsMarble Cognition raises $3.75M for its AI agent workers that watch and learn how people work
Artificial intelligence agents have become two a penny in the enterprise today, but just because they’re rapidly being commoditized does not mean organizations know how best to use them. That’s the challenge a startup ca…
- arXiv cs.AIagentsMore Rules, Longer Lists? Benchmarking Self-Evolving Agents on a Hidden-Rule Curriculum
arXiv:2610.40758v1 Announce Type: new Abstract: Self-evolving agents rewrite a persistent state from feedback, but it is largely untested whether this lets them learn a rule nobody told them. An agent can also pass by wr…
- arXiv cs.AIagentsBeyond Plausible Prediction: Safety Sufficiency in Web World Models
arXiv:2610.40798v1 Announce Type: new Abstract: Web world models increasingly predict the consequences of candidate actions before agents act, yet a plausible predicted future does not necessarily support the correct saf…
- arXiv cs.AIagentsChatGPT as a Surveillance Assistant? An Exploratory Case Study of AI-Assisted Surveillance Risks
arXiv:2610.40890v1 Announce Type: new Abstract: Large language models (LLMs) can generate detailed guidance, functional code, and persuasive text at scale. As one of the most widely used consumer language model products…
- arXiv cs.AIagentsDoes Recursive Knowledge Construction Help Agents Verify Consensus Claims in Science?
arXiv:2610.40906v1 Announce Type: new Abstract: Recent scientific agents build knowledge recursively by retrieving evidence, constructing an intermediate state, and judging whether that state contains sufficient informat…
- arXiv cs.AIagentsTowards Portable Specification of the Agent Harness
arXiv:2610.40917v1 Announce Type: new Abstract: Large language models act only through the infrastructure that surrounds them. That infrastructure, the harness, determines what a model can accomplish and how it fails, ye…
- arXiv cs.AIagentsAgentic World Modeling for Agent Test-time Scaling without Environment Replica
arXiv:2610.40927v1 Announce Type: new Abstract: Test-time scaling (TTS) improves large language model agents by sampling and selecting among multiple candidate trajectories, but common realizations assume that these traj…
- arXiv cs.AIagentsThe First Few Tokens Matter: Understanding Chain-of-Thought Controllability
arXiv:2610.40939v1 Announce Type: new Abstract: Chain-of-thought (CoT) monitoring is a promising way to oversee increasingly capable agents. It succeeds in part because current models appear limited in their ability to c…
- arXiv cs.AIagentsBenchmarking Forecasting Agents on Yesterday's Tomorrows
arXiv:2610.40940v1 Announce Type: new Abstract: Digital agents can now gather and organize information, reason over it, and use tools to complete complex tasks. Forecasting puts all of these abilities to the test: it req…
- arXiv cs.AIagentsP-ContextBench: From Personal Fact Recall to Personalized Agent Behavior
arXiv:2610.40959v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for personal tasks, yet evaluating their safe use of personal context remains difficult because such contexts are private…
- arXiv cs.AIagentsThe psychophysics of affect in large language models
arXiv:2610.40985v1 Announce Type: new Abstract: Good decisions often require considering how outcomes will feel. Yet large language models (LLMs) increasingly enter decision workflows, despite little being known about ho…
- arXiv cs.AIagentsReplayRCA: Measuring Post-hoc Diagnosis and Live Oversight of Agent Failures by Counterfactual Replay
arXiv:2610.41025v1 Announce Type: new Abstract: When a language-model agent fails a multi-step task, can another model find the decisive mistake and fix it with a single action? We introduce ReplayRCA, a benchmark that s…
- arXiv cs.AIagentsCapability-Grounded Agentic Planning
arXiv:2610.41040v1 Announce Type: new Abstract: LLM agents serve natural-language requests through tools, data sources, and other agents, and even simple requests often need several interdependent calls. Typically, the L…
- arXiv cs.AIagentsConsensus Within, Competition Between: Decentralized LLM Teams for Perimeter Defense
arXiv:2610.41044v1 Announce Type: new Abstract: The use of large language models (LLMs) to coordinate multi-agent teams raises a fundamental architectural question: whether task allocation should be centralized in a sing…
- arXiv cs.AIagentsLanG 2.0: Energy-Efficient Agentic AI for Semi-Automated Security Operations at Scale
arXiv:2610.41072v1 Announce Type: new Abstract: Security operations centers (SOCs) need to turn terabytes of alerts, logs and flows into trusted, affordable decisions to unveil hidden threats. We present LanG 2.0, an age…
- arXiv cs.AIagentsBABA-Bench: Evaluating Long-Horizon Patient-Advocacy Agents
arXiv:2610.41076v1 Announce Type: new Abstract: An LLM agent that helps a patient get care must do two things. It must reach the correct outcome, and it must follow the necessary procedure. For example, the agent must ge…
- arXiv cs.AIagentsVerifying Text-to-SQL Queries under Changing Business Semantics
arXiv:2610.41090v1 Announce Type: new Abstract: In text-to-SQL and AI-agent analytics, successful SQL execution does not establish semantic correctness under changing business definitions. We study revalidation of fixed…
- arXiv cs.AIagentsConfident Fools or Careful Searchers? A Behavioural Study of When LLMs Search Beyond Their Static Internal Memory
arXiv:2610.41124v1 Announce Type: new Abstract: Agentic LLM assistants must repeatedly decide whether to answer from memory or to call a tool such as web search. Unnecessary searches cost latency and money; missing ones…
- arXiv cs.AIagentsWhen Should AI Agents Ask? Clarification Requests Under Limited Human Attention
arXiv:2610.41129v1 Announce Type: new Abstract: AI agents increasingly carry out delegated tasks in parallel, with one person overseeing several of them at once. In practice, an agent often lacks information its task req…
- arXiv cs.AIagentsCounterfactual Pairwise Augmentation Improves Small Pointwise LLM Judges
arXiv:2610.41149v1 Announce Type: new Abstract: Agentic systems increasingly gate individual steps with a pointwise judge that scores a response against a criterion. Small language models are attractive for this role bec…
- arXiv cs.AIagentsMEMIG: Self-evolving Memory Construction for Antibody Optimization
arXiv:2610.41245v1 Announce Type: new Abstract: Memory has become central to self-evolving LLM agents, which store and retrieve experience from past rollouts to guide future decisions. Existing systems represent this exp…
- arXiv cs.AIagentsRome Wasn't Built in One Turn: Replay-Grounded Reward Signals for Long-Horizon Freeciv Agents
arXiv:2610.41264v1 Announce Type: new Abstract: Training language-model agents to play long-horizon strategy games is hard because deterministic feedback is sparse and often arrives only at the end of a game. In-game sco…
- arXiv cs.AIagentsFrom 1D Benchmarks to Complex 3D Geometries: Can Agents Reliably Specify Problems for Automated PDE Simulation?
arXiv:2610.41267v1 Announce Type: new Abstract: Turning an engineering request into a simulation requires consistent geometry, physics, boundary conditions, and numerical settings. Recent agent-assisted systems automate…
- arXiv cs.AIagentsOperon-S1: a fast decision controller for long-horizon biomedical agents
arXiv:2610.41350v1 Announce Type: new Abstract: Language-model agents now carry out long scientific work in biology, but their judgements about conventions, skills, errors, evidence and stopping are made inside the reaso…
- arXiv cs.AIagentsAsk on Demand: Targeted Peer Communication for Parallel Agentic Systems
arXiv:2610.41378v1 Announce Type: new Abstract: Parallel LLM agents tackle complex tasks by exploring multiple trajectories, yet useful discoveries remain isolated in individual execution histories. Existing sharing meth…
- arXiv cs.AIagentsCross-Interface Authorization for AI Computer-Use Agents
arXiv:2610.41397v1 Announce Type: new Abstract: Computer-use agents act through graphical interfaces, command lines, APIs, scripts, and Model Context Protocol servers. A policy decision can be interface-invariant while i…
- arXiv cs.AIagentsEvidence-Guided Recovery for AI Agents with Ambiguous Tool Outcomes and Partial Execution
arXiv:2610.41453v1 Announce Type: new Abstract: Tool timeouts can leave AI agents facing ambiguous tool outcomes and partial execution: an action may have failed, committed or remained in flight while other workflow step…
- arXiv cs.AIagentsEvoMCP: Co-evolving MCP agents and training data
arXiv:2610.41479v1 Announce Type: new Abstract: Supervised fine-tuning of Model Context Protocol (MCP) agents is typically conducted on a static data distribution, which fails to adapt to the student's evolving capabilit…
- arXiv cs.AIagentsVerify--Backtrack Loop: Structured Precondition Recovery for Long-Horizon Language Agents
arXiv:2610.41564v1 Announce Type: new Abstract: Language agents increasingly tackle long-horizon tasks in interactive environments, where actions often depend on latent preconditions. The core difficulty is not trajector…
- arXiv cs.AIagentsReal Computation or Merely Naming? A Pre-Registered Mechanism Audit of 25 Cognitive-Architecture Modules in an LLM-Based Agent System
arXiv:2610.41604v1 Announce Type: new Abstract: Agent systems built on local large language models are increasingly marketed through the vocabulary of cognitive architecture: modules named global workspace, theory of min…
- arXiv cs.AIagentsChance-Constrained Inspection Viewpoint Sequencing for On-Orbit Servicing via Safe Reinforcement Learning
arXiv:2610.41639v1 Announce Type: new Abstract: Autonomous inspection of a target spacecraft is typically the initial step in on-orbit servicing. Planning close-proximity observation viewpoints involves a complex combina…
- arXiv cs.AIagentsTSBPO: Tree-Structured Branching for Policy Optimization in Interactive Language Agents
arXiv:2610.41697v1 Announce Type: new Abstract: Training interactive language agents from terminal outcomes poses three coupled problems: which task and state continuations to sample, how to assign delayed feedback to de…
- arXiv cs.AIagentsClinical-Protocol-Aware Cyber Resilience for Connected Clinical Technologies Under AI-Enabled Adversarial Conditions
arXiv:2610.41784v1 Announce Type: new Abstract: Healthcare increasingly relies on connected medical devices, clinical information systems, cloud services, and distributed-care technologies, creating cybersecurity risks a…
- arXiv cs.AIagentsLearning to Interact and Direct: Co-Evolving Video Director Agents
arXiv:2610.41865v1 Announce Type: new Abstract: Video director agents orchestrate multistage production to realize users' creative visions. Emerging research on their self-evolution advances screenplay planning effective…
- arXiv cs.AIagentsStructure-Aware Skill Retrieval and Arbitration for Optimization Modeling
arXiv:2610.41909v1 Announce Type: new Abstract: Large Language Models (LLMs) can turn natural-language optimization tasks into solver-checked answers, but current agents remain brittle under narrative rewrites and often…
- arXiv cs.AIagentsTradeWar: A Benchmark for Execution-Grounded Trade Negotiation with Adaptive LLM Agents
arXiv:2610.42004v1 Announce Type: new Abstract: Multi-turn negotiation remains a challenging problem for large language model (LLM) agents. While LLMs can conduct natural-language dialogue, existing benchmarks predominan…
- arXiv cs.AIagentsLatent Sparse Attention: Towards Subquadratic Ultra-Long Context Attention
arXiv:2610.42147v1 Announce Type: new Abstract: Agentic workflows are increasingly shifting towards long-horizon tasks, such as open-ended scientific work, where models benefit from long context windows. However, at ultr…
- arXiv cs.AIagentsPrivacyFlow: Privacy in AI Agents through Information Flow Analysis and Consequence-Aware Risk Management
arXiv:2610.40714v1 Announce Type: cross Abstract: Autonomous LLM agents executing multi-step workflows over personal data often misalign with user privacy expectations and leak sensitive, out-of-context information. Alth…
- arXiv cs.AIagentsCharacterizing LLM Agent Behaviors in Module Shadowing Environments
arXiv:2610.40716v1 Announce Type: cross Abstract: LLM agents operating in untrusted workspaces face the risk of untrusted code execution during routine tasks, yet final reports and workspace states alone cannot reliably…
- arXiv cs.AIagentsMetaVul: Agentic Harness Discovery for Vulnerability Detection
arXiv:2610.40721v1 Announce Type: cross Abstract: LLM agents are increasingly used to automate vulnerability detection, but reliable detection is challenging because agents must distinguish subtle, security-relevant fixe…
- arXiv cs.AIagents"Shall We Approve?" Consequence-Aware Approval for Autonomous Coding Agents
arXiv:2610.40753v1 Announce Type: cross Abstract: Coding agents increasingly rely on automated approvers to decide whether a proposed shell command may run. Existing approvers, from rule-based checkers to guardrail model…
- arXiv cs.AIagentsTSFLab: A Self-Improving Agent-Agnostic Workbench for Time Series Forecasting Research
arXiv:2610.40901v1 Announce Type: cross Abstract: As publications and products on time series forecasting (TSF) proliferate, researchers face a growing burden of analyzing existing work. First, not all publications relea…
- arXiv cs.AIagentsAccept Changes, Reject Attacks: Robust Memory Management for LLM Agents
arXiv:2610.41056v1 Announce Type: cross Abstract: Since large language model (LLM) agents rely on long-term memory, what they store now shapes what they do later. A memory manager decides how each input changes this memo…
- arXiv cs.AIagentsWhen Disclosure Is Compulsory: Evaluating Ride-Hailing Rebalancing Policies with Self-Interested LLM Driver Agents
arXiv:2610.41132v1 Announce Type: cross Abstract: The EU Platform Work Directive, to be transposed by December 2026, requires ride-hailing platforms to state in plain language the main parameters of their automated decis…
- arXiv cs.AIagentsContext as Infrastructure: Knowledge Compilation for Retrieval in Agentic Systems with Harnesses
arXiv:2610.41172v1 Announce Type: cross Abstract: Retrieval-augmented generation is becoming agentic. A search harness writes queries, reads results, reformulates, and decides when to stop. This largely solves accuracy:…
- arXiv cs.AIagentsANGLER: Verifier-Grounded Benchmarking with an Adaptive Attacker for Web Agents
arXiv:2610.41272v1 Announce Type: cross Abstract: Web agents are increasingly deployed to complete tasks autonomously on real websites, where adversarially injected content can induce them to perform unauthorized actions…
- arXiv cs.AIagentsIn-Model Context Compression with Agentic Soft Tokens for Long-Horizon LLM Agents
arXiv:2610.41291v1 Announce Type: cross Abstract: Long-horizon LLM agents play an important role in solving complex and sustained tasks, with ever-growing interaction contexts. However, these accumulated contexts will ra…