AI news archive.
4,965 articles filed under Agents, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsQD-Rec: Open-Ended Evolution of Recommendations via Quality-Diversity
arXiv:2610.23470v2 Announce Type: replace-cross Abstract: Open-ended search combined with foundation models has produced advances such as faster algorithms, new results on open mathematical problems, and self-improving a…
- arXiv cs.AIagentsFrom Billion-Scale to Million-Scale Language Models: Operational Capabilities for Embedded Post-Exploitation
arXiv:2610.23534v1 Announce Type: cross Abstract: Small Language Models (SLMs) are increasingly attractive for resource-constrained environments due to their low computational footprint. These characteristics also make t…
- arXiv cs.AIagentsSIT-Eval: Situation-Based Interactive Turn-by-Turn Evaluation of Conversational Agents
arXiv:2610.23612v1 Announce Type: cross Abstract: The rapid proliferation of conversational AI agents necessitates evaluation methods that assess performance across diverse dialogue scenarios, utilizing multiple situatio…
- arXiv cs.AIagentsOn the possibilities and limitations of LLM-based multi-agent systems for multi-criteria decision-making in healthcare operations management
arXiv:2610.23673v1 Announce Type: cross Abstract: Multi-criteria models for healthcare operations need weights that express how stakeholders trade off patient waiting time, provider workload, and operating cost, but thes…
- arXiv cs.AIagentsGLOBE: Evolving Structured Agentic Memory for E-commerce Product Optimization in Generative Search
arXiv:2610.23709v1 Announce Type: cross Abstract: Optimizing product listings for generative search requires language agents not only to rewrite effectively but also to continually self-improve by retaining successful st…
- arXiv cs.AIagentsComputational Multi-Agents Society Experiments: Social Modeling Framework Based on Generative Agents
arXiv:2508.17366v3 Announce Type: replace Abstract: Computational social science has developed descriptive, interpretative, and predictive modeling, but comprehensive modeling combining in-world human intervention with o…
- arXiv cs.AIagentsTowards Unified World Models for Visual Navigation via Memory-Augmented Planning and Foresight
arXiv:2510.08713v4 Announce Type: replace Abstract: Enabling embodied agents to imagine future states is essential for robust and generalizable visual navigation. Yet, state-of-the-art systems typically rely on modular d…
- arXiv cs.AIagentsNEXUS: Learning Safety Constraints and Action Models for Safe and Robust Embodied Planning
arXiv:2605.09387v2 Announce Type: replace Abstract: Large language models (LLMs) enable embodied agents to plan from naturallanguage instructions, yet their actions may be physically infeasible or hazardous. Existing neu…
- arXiv cs.AIagentsATWL: A Formal Language for Representing, Comparing, and Reusing Visual Analytics Workflows
arXiv:2605.25489v2 Announce Type: replace Abstract: Visual analytics (VA) workflows combine data transformation, feature computation, visual representation, and human interpretation, but they are usually described in pro…
- arXiv cs.AIagentsPrompt Codebooks: Discrete Compositional Optimization for Language Model Instruction Refinement
arXiv:2605.28360v3 Announce Type: replace Abstract: Automatic prompt optimization (APO) has driven significant gains in LLM-based agentic workflows. However, most existing methods treat each task's prompt as a monolithic…
- arXiv cs.AIagentsBeyond Semantic Organization: Memory as Execution State Management for Long-Horizon Agents
arXiv:2606.06090v2 Announce Type: replace Abstract: LLM-based agents increasingly tackle long-horizon tasks with interdependent decisions, where each action reshapes future constraints and intermediate errors can cascade…
- arXiv cs.AIagentsAPeB: Benchmarking Personalization Ability of Large Language Model Agents
arXiv:2607.03162v3 Announce Type: replace Abstract: LLM-powered agents struggle with personalization when users issue raw, underspecified queries. In this setting, agents must infer latent intent, extract preferences fro…
- arXiv cs.AIagentsAlign AI to Dynamic Human-AI Workflows
arXiv:2607.14240v2 Announce Type: replace Abstract: Current alignment approaches typically focus on emulating human behavior using static representations of human preferences, failing to capture the dynamic, context-depe…
- arXiv cs.AIagentsQ-Reflector: Learning GUI Action Reflection with Generated Conditions
arXiv:2608.05587v2 Announce Type: replace Abstract: Mobile GUI agents require accurate action reflection for reliable long-horizon execution, assessing whether each action was successfully executed and whether its outcom…
- arXiv cs.AIagentsTeach the Magnitude, Not the Direction: Verifier-Anchored Credit Assignment for Multi-Turn Multi-Step LLM Agents
arXiv:2608.13179v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) directly optimizes verifier-defined outcomes for multi-turn tool-use agents, yet its trajectory-level credit assig…
- arXiv cs.AIagentsBeyond Uncertainty Reduction: Calibrated Planning for Interactive Diagnosis
arXiv:2608.27847v2 Announce Type: replace Abstract: Interactive medical diagnosis requires an agent to gather patient evidence through sequential questions before committing to a diagnosis. Large language models (LLMs) n…
- arXiv cs.AIagentsCollaborating with AI Agents: Field Experiments on Teamwork, Productivity, and Performance
arXiv:2503.18238v4 Announce Type: replace-cross Abstract: We examined the mechanisms underlying productivity and performance gains from AI agents using a large-scale experiment on Pairit, a platform we developed to study…
- arXiv cs.AIagentsOperon: Incremental Construction of Ragged Data via Named Dimensions
arXiv:2511.16080v3 Announce Type: replace-cross Abstract: Modern data processing workflows frequently encounter ragged data: multidimensional collections whose inner lengths vary and are revealed only at runtime. Ragged…
- arXiv cs.AIagentsVeri-Sure: Multi-Agent RTL Code Generation with Temporal Tracing, Slicing and Formal Verification
arXiv:2601.19747v2 Announce Type: replace-cross Abstract: In the rapidly evolving field of Electronic Design Automation (EDA), the deployment of Large Language Models (LLMs) for Register-Transfer Level (RTL) code generat…
- arXiv cs.AIagentsA Theoretical Analysis of Test-Driven Code Generation
arXiv:2602.06098v4 Announce Type: replace-cross Abstract: Code assistants are increasingly utilized in test-driven software development, yet the theoretical mechanisms behind their environment-interaction strategies rema…
- arXiv cs.AIagentsLanguage Model Goal Selection Differs from Humans' in a Self-Directed Learning Task
arXiv:2603.03295v3 Announce Type: replace-cross Abstract: Whether in agentic workflows, social studies, or chat settings, large language models (LLMs) are increasingly being asked to replace humans in choosing which goal…
- arXiv cs.AIagentsAOI: Turning Failed Trajectories into Training Signals for Autonomous Cloud Diagnosis
arXiv:2603.03378v4 Announce Type: replace-cross Abstract: Large language model (LLM) agents offer a promising data-driven approach to automating Site Reliability Engineering (SRE), yet their enterprise deployment is cons…
- arXiv cs.AIagentsCastFlow: Bridging Evidence Acquisition and Accurate Prediction in Agentic Time Series Forecasting
arXiv:2604.27840v3 Announce Type: replace-cross Abstract: Time series forecasting is a fundamental task in temporal data analytics, and large language model (LLM)-based agents offer a promising paradigm through autonomou…
- arXiv cs.AIagentsCoordination Matters: Process-Aware Evaluation of Cooperative Multi-Agent Reinforcement Learning
arXiv:2605.06557v2 Announce Type: replace-cross Abstract: Cooperative multi-agent reinforcement learning (MARL) benchmarks commonly emphasize aggregate outcomes such as return, success rate, or completion time. While ess…
- arXiv cs.AIagentsAgentRivet: an automated system for producing Rivet routines from journal publications
arXiv:2606.13535v5 Announce Type: replace-cross Abstract: Particle physics collider experiments provide Rivet routines as part of the analysis preservation strategy for model-independent measurements. Rivet is a C++ tool…
- arXiv cs.AIagentsGroup-Graph Policy Optimization for Long-Horizon Agentic Reinforcement Learning
arXiv:2606.22995v2 Announce Type: replace-cross Abstract: Group-based Reinforcement Learning (RL) has significantly enhanced Large Language Models (LLMs) in agentic scenarios. To achieve finer-grained policy updates, rec…
- arXiv cs.AIagentsDo Multi-Agent LLMs Explore Each Other?
arXiv:2607.11250v2 Announce Type: replace-cross Abstract: Exploration is essential for reliable autonomy in multi-agent systems, yet it remains unclear whether large language model (LLM) agents can explore effectively wh…
- arXiv cs.AIagentsHow Agents Ask for Permission: User Permissions for AI Agents, from Interfaces to Enforcement
arXiv:2607.13718v3 Announce Type: replace-cross Abstract: As AI agents grow in prevalence, so too do their risks to users, creating a need for robust and usable systems for agent permissions. Many recent proposals implem…
- arXiv cs.AIagentsEvery Model Cheats: Prompt-Level Mitigation of Cheating on Offensive Cyber Tasks
arXiv:2607.21763v2 Announce Type: replace-cross Abstract: Large language model (LLM) agents routinely cheat on cybersecurity benchmarks, inflating reported pass rates far beyond genuine capability. Prior audits of Cybenc…
- arXiv cs.AIagentsTowards Agentic Cloud Engineering: Graph and Loop Engineering with a Zero-Trust Agent Harness
arXiv:2609.00050v2 Announce Type: replace-cross Abstract: Agentic AI is enabling cloud-based workflows in which autonomous agents reason over operational state, invoke authorized tools, modify software and infrastructure…
- arXiv cs.AIagentsDoing Less with More: A First-Principles Exploration of the Suitability of Agentic Computing over Alternative Architectural Choices
arXiv:2610.23921v1 Announce Type: new Abstract: There is growing interest in automating business activities with Agentic Artificial Intelligence (AI) due to latter's seeming ease of use. Never has it been easier, or cost…
- arXiv cs.AIagentsA Controlled LLM Workflow for Evidence-Grounded Diagnosis of Risk Score Differences
arXiv:2610.23962v1 Announce Type: new Abstract: We propose a controlled Large Language Model (LLM) workflow for explaining risk score differences using similar historical transactions. The workflow combines reference ret…
- arXiv cs.AIagentsWorld of SWECraft: Agent Collaboration at Scale via Simulated Software Worlds
arXiv:2610.24061v2 Announce Type: replace Abstract: As teams of AI agents take on larger projects and long-standing open problems, agent collaboration offers another dimension for scaling inference-time compute. To under…
- arXiv cs.AIagentsPersistent Memory and Iterative Improvement in an LLM Agent for Chinese-Character Drawing
arXiv:2610.24090v1 Announce Type: new Abstract: Does persistent memory accumulated from previous attempts help an LLM agent solve new problems, and does memory design affect that benefit? We study programmatic Chinese-ch…
- arXiv cs.AIagentsJoint, Decoupled, or Agent: When Each Multimodal Alignment Paradigm Wins
arXiv:2610.24108v1 Announce Type: new Abstract: Jointly pretrained multimodal encoders are a common way to combine modalities, while alternatives integrate their information during downstream training or inference. When…
- arXiv cs.AIagentsSelf-Improving Video-to-Action Models
arXiv:2610.24177v1 Announce Type: new Abstract: Video generative models are an emerging tool for embodied agents: they can serve as scalable visual planners, generating videos that depict how to complete previously unsee…
- arXiv cs.AIagentsAgents' Last Doubt: Knowing When to Act and When to Step Back in Tool-Using Agents
arXiv:2610.24194v1 Announce Type: new Abstract: Tool-using LLM agents repeatedly face decision points under uncertainty, choosing between autonomous action, additional information gathering, and human escalation. These d…
- arXiv cs.AIagentsCortex: A Fixed-Point Theory of Governed Coding Agents - Technical Report
arXiv:2610.24255v1 Announce Type: new Abstract: A coding agent combines a large language model (LLM) with a harness that plans, edits, and executes code. We study Cortex, a supervisory layer for pre-execution governance,…
- arXiv cs.AIagentsAM-Bench: A Unified Taxonomy and Evaluation Suite for Agentic Misalignment
arXiv:2610.24264v3 Announce Type: replace Abstract: As LLM-based agents are deployed with increasing autonomy in real-world environments, a critical failure mode emerges: agentic misalignment, where agents choose harmful…
- arXiv cs.AIagentsSteerSearch: Interactive Search Reasoning with Mid-Response Steering
arXiv:2610.24287v1 Announce Type: new Abstract: Search-augmented language models increasingly serve as long-horizon research agents, yet most open training methods assume a fixed user goal throughout search. We study mid…
- arXiv cs.AIagentsNot Every User Says It All: Training Tool-Using Agents Beyond Ideal Simulated Users
arXiv:2610.24294v1 Announce Type: new Abstract: Tool-using agents are trained and evaluated almost exclusively with strong simulated users who state every detail clearly, yet real users are often weaker. We construct wea…
- arXiv cs.AIagentsWho Speaks, Who Authorizes, Who Acts? Understanding Trust Boundaries in Multi-Agent LLMs
arXiv:2610.24298v1 Announce Type: new Abstract: Multi-agent LLM systems exchange messages before acting through tools, but message delivery, signing authority, and tool-side enforcement are separate trust boundaries. We…
- arXiv cs.AIagentsTrain Locally, Learn Together: Distributed Multi-Agent Training via ADMM
arXiv:2610.24380v1 Announce Type: new Abstract: Multi-agent systems (MAS) can outperform individual language-model agents by combining specialized roles, diverse reasoning processes, and collaborative decision-making. Ho…
- arXiv cs.AIagentsIs This Your Agent? Identity Watermarking for Agent Systems in Dynamic Environments
arXiv:2610.24382v1 Announce Type: new Abstract: Agent systems deployed in dynamic environments continuously update their memories, skills, and runtime configurations, leading to evolving trajectories and challenges for p…
- arXiv cs.AIagentsIF-MAP: Influence-Function-Inspired Agent Prioritization in Multi-Agent Systems
arXiv:2610.24383v1 Announce Type: new Abstract: Improving every agent in an LLM-based multi-agent system can be prohibitively costly, making it important to identify which agent should be prioritized to achieve the great…
- arXiv cs.AIagentsBridging Exploration and Persona: Information-Directed Dueling for Test-Time Agent Personalization
arXiv:2610.24385v2 Announce Type: replace Abstract: Effective test-time personalization requires LLM agents to adapt to query-dependent user preferences from lightweight interaction. We study persona selection with binar…
- arXiv cs.AIagentsHippo: Training-Free Agent Self-Evolution via Hippocampal Replay
arXiv:2610.24453v2 Announce Type: replace Abstract: Motivated by recursive self-improvement (RSI), we study how LLM agents can learn through external memory without updating model parameters. Extracting useful experience…
- arXiv cs.AIagentsMELD: Recursive Self-Improvement via Hierarchical Coordination for Multi-Agent Scientific Discovery
arXiv:2610.24454v1 Announce Type: new Abstract: Multi-agent scientific discovery with large language models raises a coupled learning problem: research assignments determine both which experiments are pursued and the exp…
- arXiv cs.AIagentsHABIT-Bench: Evaluating Habit Induction from Longitudinal Weak Evidence in Agent Memory
arXiv:2610.24520v2 Announce Type: replace Abstract: In long-term interactions with large language model (LLM) agents, users reveal habits through their choices and actions. These habits capture implicit user information…
- arXiv cs.AIagentsHSPR: Recovering Software-Agent Benchmark Scores via Hierarchical Posterior Inference
arXiv:2610.24611v2 Announce Type: replace Abstract: Evaluating software agents on a full benchmark is expensive. A small task subset can preserve agent rankings while yielding inaccurate scores. Historical responses prov…