AI news archive.
4,966 articles filed under Agents, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsAgentic Explainable Artificial Intelligence (Agentic XAI) Approach To Explore Better Explanation: A Case Study in Decision Support for Rice Cultivation in Japan
arXiv:2512.21066v4 Announce Type: replace Abstract: Explainable artificial intelligence (XAI) reveals how explanatory variables relate to a response variable, yet communicating XAI outputs to laypersons remains difficult…
- arXiv cs.AIagentsA Survey of Agentic Reasoning for Large Language Models: Towards Recursively Self-Improving and Collective Agents
arXiv:2601.12538v2 Announce Type: replace Abstract: Reasoning is a fundamental cognitive process underlying inference, problem-solving, and decision-making. While large language models (LLMs) demonstrate strong reasoning…
- arXiv cs.AIagentsReplayable Financial Agents: A Determinism-Faithfulness Assurance Harness for Tool-Using LLM Agents
arXiv:2601.15322v4 Announce Type: replace Abstract: Replaying a financial agent requires specifying the conditions of a rerun, preserving its execution record, and deciding which parts of its behavior to compare. We intr…
- arXiv cs.AIagentsSTRUCTUREDAGENT: Planning with AND/OR Trees for Long-Horizon Web Tasks
arXiv:2603.05294v3 Announce Type: replace Abstract: Existing LLM-based web agents struggle on complex, long-horizon tasks due to limited in-context memory, weak planning abilities, and greedy behaviors that lead to prema…
- arXiv cs.AIagentsThe Self Driving Portfolio: Agentic Architecture for Institutional Asset Management
arXiv:2604.02279v2 Announce Type: replace Abstract: Agentic AI shifts the investor's role from analytical execution to oversight. We present an agentic strategic asset allocation pipeline in which 44 specialized agents p…
- arXiv cs.AIagentsCivBench: Progress-Based Evaluation for LLMs' Strategic Decision-Making in Civilization V
arXiv:2604.07733v2 Announce Type: replace Abstract: Evaluating strategic decision-making in LLM-based agents requires generative, competitive, and longitudinal environments, yet few benchmarks provide all three, and fewe…
- arXiv cs.AIagentsAn Analysis of the Coordination Gap between Joint and Modular Learning for Job Shop Scheduling with Transportation Resources
arXiv:2604.24117v3 Announce Type: replace Abstract: Efficient job-shop scheduling with transportation resources is critical for high-performance manufacturing. With the rise of "decentralized factories", multi-agent rein…
- arXiv cs.AIagentsCoFlow: Coordinated Few-Step Flow for Offline Multi-Agent Decision Making
arXiv:2605.01457v4 Announce Type: replace Abstract: How can generative offline multi-agent reinforcement learning achieve both fast joint trajectory generation and effective cooperation? Multi-agent diffusion models gene…
- arXiv cs.AIagentsToolCUA: Towards Optimal GUI-Tool Path Orchestration for Computer Use Agents
arXiv:2605.12481v2 Announce Type: replace Abstract: Computer Use Agents (CUAs) can act through both atomic GUI actions, such as click and type, and high-level tool calls, such as API-based file operations, but this hybri…
- arXiv cs.AIagentsReliability and Effectiveness of Autonomous AI Agents in Supply Chain Management
arXiv:2605.17036v4 Announce Type: replace Abstract: This paper studies the performance and reliability of autonomous generative AI agents in multi-echelon supply chains using the MIT Beer Game. We examine how model choic…
- arXiv cs.AIagentsPTCG-Bench: Can LLM Agents Master Pok\'emon Trading Card Game?
arXiv:2605.29653v2 Announce Type: replace Abstract: Given a strategically complex board game, human players can quickly learn to devise strategies after playing a few rounds. Autonomous agents require similar capabilitie…
- arXiv cs.AIagentsCan Generalist Agents Automate Data Curation?
arXiv:2606.04261v2 Announce Type: replace Abstract: Curating training data is among the most consequential yet labor-intensive parts of modern AI development: practitioners iteratively propose, implement, evaluate, and r…
- arXiv cs.AIagentsHow Far Did They Go? The Persuasive Tactics of Covert LLM Agents in a Discontinued Field Experiment
arXiv:2606.05256v2 Announce Type: replace Abstract: This study analyzes a publicly released dataset from a discontinued field experiment on Reddit's r/ChangeMyView. The intervention, conducted by unknown, external resear…
- arXiv cs.AIagentsDecision-Aware Memory Cards: Counterfactual-Inspired Context Selection and Compression for Tool-Using LLM Agents
arXiv:2606.08151v4 Announce Type: replace Abstract: Modern large language model (LLM) agents do not simply need longer contexts; they need decision-relevant evidence at the moment of action. We study decision-aware conte…
- arXiv cs.AIagentsTo Nuke or Not to Nuke: LLMs' (Missing) Ethical Reasoning and Actions in a High-Stakes Decision-Making Simulation
arXiv:2606.08310v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed as long-horizon agents with decision-making capacities. While LLMs can show ethical competence on dilemmas such a…
- arXiv cs.AIagentsMDForge: Agentic Molecular Dynamics Pipeline Design under Sparse Simulator Feedback
arXiv:2606.12916v2 Announce Type: replace Abstract: Molecular dynamics (MD) is the canonical in-silico method for atomistic molecular science, simulating molecular behavior from first-principle physics. Designing an MD p…
- arXiv cs.AIagentsENPIRE: Agentic Robot Policy Self-Improvement in the Real World
arXiv:2606.19980v2 Announce Type: replace Abstract: Achieving dexterous robotic manipulation in the real world heavily relies on human supervision and algorithm engineering, which becomes a central bottleneck in the purs…
- arXiv cs.AIagentsScoped Verification for Reliable Long-Horizon Agentic Context Evolution under Distribution Shift
arXiv:2607.09175v2 Announce Type: replace Abstract: Deployed LLM agents rely on agentic context, the model-external textual control content assembled by an operational harness. In this work, the mutable component of that…
- arXiv cs.AIagentsMeasure the Sim-to-Real Gap: Designing an Affordable Real-World Benchmark Platform for Reinforcement Learning in AIoT Systems
arXiv:2607.10309v3 Announce Type: replace Abstract: Reinforcement learning (RL) is commonly employed to enhance the performance of autonomous systems, including the Autonomous Internet of Things (AIoT). However, the tria…
- arXiv cs.AIagentsLarge language models for partial differential equation workflows
arXiv:2608.03600v3 Announce Type: replace Abstract: Numerical methods and deep learning have advanced the modelling and simulation of systems governed by partial differential equations (PDEs), while formulating equations…
- arXiv cs.AIagentsTARL: Transaction-Aware Reliable Ledgers for Executable Memory Management in Long-Term Agents
arXiv:2608.03699v5 Announce Type: replace Abstract: Persistent memory helps long-term agents retain knowledge, yet a single update error can repeatedly distort future retrieval and reasoning. Most existing systems reduce…
- arXiv cs.AIagentsInfraBench: Evaluating Infrastructure Agents Across Layers, Lifecycle, and Risk
arXiv:2608.11234v4 Announce Type: replace Abstract: Managing modern computing infrastructure has become a steadily harder problem due to the ever-increasing complexity. Recent advances in AI agents create a timely opport…
- arXiv cs.AIagentsLongRCA Bench: Root-Cause Localization in Long-Horizon Agent Trajectories
arXiv:2608.15242v4 Announce Type: replace Abstract: In long agent executions, an early error can persist through later actions and checks, while evidence needed to trace its origin is dispersed across the history. Short…
- arXiv cs.AIagentsVIALS: A Benchmark for Visual Interpretation of Artifacts in the Life Sciences
arXiv:2608.21357v2 Announce Type: replace Abstract: In professional life sciences workflows, scientists routinely interpret visual artifacts (gel blots, microscopy images, plasmid maps, flow cytometry plots, molecular st…
- arXiv cs.AIagentsRobustSGPO: Search-Space Control for Agent Harness Evolution
arXiv:2609.09646v2 Announce Type: replace Abstract: Semantic-gradient-based prompt optimization (SGPO) improves agent harnesses using execution feedback, but its local update rule leaves the choice of edit scope and oper…
- arXiv cs.AIagentsMagenta: Closing the Loop Between Mathematical Reasoning and Lean Verification
arXiv:2609.11319v2 Announce Type: replace Abstract: Most of mathematical knowledge has been communicated through so-called informal use of mathematics and natural language. With large language models (LLMs) being highly…
- arXiv cs.AIagentsZGCM-1: A Fully Open and Extremely Efficient Foundation Model for Math and Agentic Search
arXiv:2609.13356v2 Announce Type: replace Abstract: In this work, we present ZGCM-1, a fully open 7B dense foundation model trained from scratch with extreme data, system, and algorithmic efficiency. ZGCM-1 is founded on…
- arXiv cs.AIagentsRSIAgent: Autonomous Exploration for Recursive Self-improvement in New Environments
arXiv:2609.15364v2 Announce Type: replace Abstract: Digital agents must often adapt to new environments whose interfaces, tools, and failure modes are not fully captured by pretrained models. We introduce \textbf{RSIAgen…
- arXiv cs.AIagentsCADWorld: Computer-Use Benchmark for Long-Horizon Computer-Aided Design
arXiv:2609.16251v2 Announce Type: replace Abstract: Computer-use agents are increasingly evaluated in realistic desktop environments, but existing benchmarks provide limited coverage of professional engineering workflows…
- arXiv cs.AIagentsJustFit: Just-in-Time State Management for Local LLM Serving
arXiv:2609.17475v3 Announce Type: replace Abstract: Local agents need memory for model execution and working history. We present JustFit, an MLX runtime that coordinates their overlapping allocations: KVExec executes and…
- arXiv cs.AIagentsEnhancing Autonomous Driving Safety through World Model-Based Predictive Navigation and Adaptive Learning Algorithms for 5G Wireless Applications
arXiv:2411.15042v3 Announce Type: replace-cross Abstract: Addressing the challenge of ensuring safety in ever-changing and unpredictable environments, particularly in the swiftly advancing realm of autonomous driving in…
- arXiv cs.AIagentsHumanAgencyBench: Scalable Evaluation of Human Agency Support in AI Assistants
arXiv:2509.08494v2 Announce Type: replace-cross Abstract: As humans delegate more tasks and decisions to artificial intelligence (AI), we risk losing control of our individual and collective futures. Relatively simple al…
- arXiv cs.AIagentsToward an Unbiased Collective Memory for Efficient LLM-Based Agentic 6G Cross-Domain Management
arXiv:2509.26200v2 Announce Type: replace-cross Abstract: Agentic artificial intelligence is a candidate enabler of Level-4 autonomy in sixth-generation (6G) networks, but agents reasoning over a shared memory inherit it…
- arXiv cs.AIagentsA Human-AI Collaborative Workflow for Mathematical Discovery: A Case Study in Grover-Compatible Riemannian Optimization
arXiv:2512.09443v3 Announce Type: replace-cross Abstract: We investigate how large language models can be used as research tools in scientific computing while preserving mathematical rigor. We propose a human-in-the-loop…
- arXiv cs.AIagents"When to Hand Off, When to Work Together": Understanding Concurrent Human-Agent Interaction in Shared Co-Creative Workspaces
arXiv:2603.02050v5 Announce Type: replace-cross Abstract: Shared co-creative workspaces allow users to contribute while agents execute. Yet how users adjust their participation as their work and the agent's execution sha…
- arXiv cs.AIagentsCognition to Control - Multi-Agent Learning for Human-Humanoid Collaborative Transport
arXiv:2603.03768v2 Announce Type: replace-cross Abstract: Full-stack human-robot collaboration (HRC) can become brittle when replacing a planner, partner model, coordination policy, or controller changes the physical mea…
- arXiv cs.AIagentsRAT: RunAnyThing via Fully Automated Environment Configuration
arXiv:2604.23190v3 Announce Type: replace-cross Abstract: Automating repository-level software engineering tasks is a foundational challenge for autonomous code agents, largely due to the difficulty of configuring execut…
- arXiv cs.AIagentsAPIOT: Autonomous Vulnerability Management Across Bare-Metal Industrial OT Networks
arXiv:2605.02346v2 Announce Type: replace-cross Abstract: Operational technology (OT) devices run safety-critical physical processes, yet their security testing remains manual and expert-intensive. Autonomous security ag…
- arXiv cs.AIagentsTraining-Free Refusal of MCP Exploits via Retrieval-Augmented Generation
arXiv:2605.11217v2 Announce Type: replace-cross Abstract: The model context protocol (MCP) has been widely adopted as an open standard enabling the seamless integration of generative AI agents. However, while LLM guardra…
- arXiv cs.AIagentsgwBenchmarks: Stress-Testing LLM Agents on High-Precision Gravitational Wave Astronomy
arXiv:2605.11269v2 Announce Type: replace-cross Abstract: Modern gravitational wave astronomy relies on modeling tasks that often require months of graduate-level effort, including building fast waveform surrogates from…
- arXiv cs.AIagentsDiscovery of Interpretable Surrogates via Agentic AI: Application to Gravitational Waves
arXiv:2605.11280v2 Announce Type: replace-cross Abstract: Fast surrogate models for expensive simulations are now essential across the sciences, yet they typically operate as black boxes. We present \texttt{GWAgent}, a l…
- arXiv cs.AIagentsCan LLMs Time Travel? Enhancing Temporal Consistency in Legal Agentic Search through Reinforcement Learning
arXiv:2605.25920v2 Announce Type: replace-cross Abstract: While large language models (LLMs) augmented with agentic search capabilities show promise for legal reasoning, they overlook a fundamental constraint that applic…
- arXiv cs.AIagentsA Taxonomy of Runtime Faults in Model Context Protocol Servers
arXiv:2606.05339v2 Announce Type: replace-cross Abstract: MCP (Model Context Protocol) enables LLMs (Large Language Models) to interact with external tools and data sources via a standardized protocol. Its rapid adoption…
- arXiv cs.AIagentsTransformer-Based Warm-Starting for Feasible and Optimal Terminal Approach to Tumbling Objects with Space Manipulators
arXiv:2606.17317v2 Announce Type: replace-cross Abstract: Autonomous capture of a tumbling object with a space manipulator requires trajectory generation under real-time onboard constraints. However, coupled bus-arm dyna…
- arXiv cs.AIagentsConnect the Dots: Training LLMs for Long-Lifecycle Agents with Cross-Domain Generalization Via Reinforcement Learning
arXiv:2606.20002v2 Announce Type: replace-cross Abstract: This work presents a general framework for training large language models (LLMs) to "Connect the Dots" (CoD), a meta-capability required by long-lifecycle agents:…
- arXiv cs.AIagentsBehavioral Skill Reconstruction: Reconstructing Hidden Functionality from LLM Agent Skills
arXiv:2608.04192v2 Announce Type: replace-cross Abstract: Closed source agent skills may encode proprietary instructions, scripts, constants, and data. Providers may offer their capabilities as services while keeping the…
- arXiv cs.AIagentsRebuild Dossier: Mechanically-Enforced Specs for Agentic App Rebuilds, and What Model-Tier Failures Reveal
arXiv:2608.23616v4 Announce Type: replace-cross Abstract: An AI agent's rebuild is only as good as the process that produced it. Prior work found that once a model is strong enough, a multi-agent rebuild pipeline loses t…
- arXiv cs.AIagentsRuntime-Independent Persistent Agents: Preserving Identity, Memory, and Code Across Models, Harnesses, and Servers
arXiv:2609.00546v2 Announce Type: replace-cross Abstract: Long-lived AI agents may replace their models, orchestration harnesses, interaction surfaces and hosts while retaining identity, memory and executable body lineag…
- arXiv cs.AIagentsInput-to-State Stability Framework for Fully Distributed Primal-Dual Dynamics for Quadratic GNEPs Without Multiplier Consensus
arXiv:2609.06983v2 Announce Type: replace-cross Abstract: Generalized Nash Equilibrium Problems (GNEPs) often arise in multi-agent engineering applications that require distributed algorithms. Unlike traditional approach…
- arXiv cs.AIagentsEcdysis: Efficient and Effective Training of Runtime Harnesses for LLM Agents
arXiv:2609.11677v2 Announce Type: replace-cross Abstract: Self-evolving runtime harnesses can substantially improve the capabilities of large language model (LLM) agents and provide a promising paradigm for optimizing ag…