Search: “agents”

PIVOT: Bridging Planning and Execution in LLM Agents via Trajectory Refinement

arXiv:2605.11225v1 Announce Type: cross Abstract: Large language model (LLM)-based agents frequently generate seemingly coherent plans that fail upon execution due to infeasible actions, constraint vi

13 May 2026

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Robust Multi-Agent Path Finding under Observation Attacks: A Principled Adversarial-Plus-Smoothing Training Recipe

DGX agent

arXiv:2605.11469v1 Announce Type: new Abstract: Decentralized multi-agent path finding (MAPF) routes a team of agents on a shared grid, each acting from its own local view. The standard solution train

safetyarxiv-cs-lg

13 May 2026

ASIA: an Autonomous System Identification Agent

arXiv:2605.10480v1 Announce Type: new Abstract: Over the years, research in system identification has provided a rich set of methods for learning dynamical models, together with well-established theor

Context Learning for Multi-Agent Discussion

arXiv:2602.02350v2 Announce Type: replace Abstract: Multi-Agent Discussion (MAD) has garnered increasing attention very recently, where multiple LLM instances collaboratively solve problems via struct

From Spark to Fire: Modeling and Mitigating Error Cascades in LLM-Based Multi-Agent Collaboration

arXiv:2603.04474v2 Announce Type: replace-cross Abstract: Large Language Model-based Multi-Agent Systems (LLM-MAS) are increasingly applied to complex collaborative scenarios. However, their collabora

HAGE: Harnessing Agentic Memory via RL-Driven Weighted Graph Evolution

arXiv:2605.09942v1 Announce Type: new Abstract: Memory retrieval in agentic large language model (LLM) systems is often treated as a static lookup problem, relying on flat vector search or fixed binar

Heteroscedastic Diffusion for Multi-Agent Trajectory Modeling

arXiv:2605.10717v1 Announce Type: cross Abstract: Multi-agent trajectory modeling traditionally focuses on forecasting, often neglecting more general tasks like trajectory completion, which is essenti

agentsarxiv-cs-cv

Iterative Critique-and-Routing Controller for Multi-Agent Systems with Heterogeneous LLMs

arXiv:2605.08686v1 Announce Type: new Abstract: Multi-agent large language model (LLM) systems often rely on a controller to coordinate a pool of heterogeneous models, yet existing controllers are typ

MAGE: Multi-Agent Self-Evolution with Co-Evolutionary Knowledge Graphs

arXiv:2605.10064v1 Announce Type: new Abstract: Self-evolving language-model agents must decide what to learn next and how to preserve what they have learned across iterations. Existing systems typica

Mechanism Design Is Not Enough: Prosocial Agents for Cooperative AI

arXiv:2605.08426v1 Announce Type: cross Abstract: Ensuring that AI agents behave safely and beneficially when interacting with other parties has emerged as one of the central challenges of modern AI s

MemReread: Enhancing Agentic Long-Context Reasoning via Memory-Guided Rereading

arXiv:2605.10268v1 Announce Type: cross Abstract: To tackle long-context reasoning tasks without the quadratic complexity of standard attention mechanisms, approaches based on agent memory have emerge

NyayaAI: An AI-Powered Legal Assistant Using Multi-Agent Architecture and Retrieval-Augmented Generation

arXiv:2605.10155v1 Announce Type: new Abstract: Legal information in India remains largely inaccessible due to the complexity of legal language and the sheer volume of legal documentation involved in

PRISM: Generation-Time Detection and Mitigation of Secret Leakage in Multi-Agent LLM Pipelines

arXiv:2605.10614v1 Announce Type: new Abstract: Multi-agent LLM systems introduce a security risk in which sensitive information accessed by one agent can propagate through shared context and reappear

Remember the Decision, Not the Description: A Rate-Distortion Framework for Agent Memory

arXiv:2605.10870v1 Announce Type: new Abstract: Long-horizon language agents must operate under limited runtime memory, yet existing memory mechanisms often organize experience around descriptive crit

Skill-CMIB: Multimodal Agent Skill for Consistent Action via Conditional Multimodal Information Bottleneck

arXiv:2605.08526v1 Announce Type: new Abstract: While LLM-based agents excel at planning and executing long action sequences, their execution often remains inconsistent across trials, limiting reliabi

Towards On-Policy Data Evolution for Visual-Native Multimodal Deep Search Agents

arXiv:2605.10832v1 Announce Type: new Abstract: Multimodal deep search requires an agent to solve open-world problems by chaining search, tool use, and visual reasoning over evolving textual and visua

WildClawBench: A Benchmark for Real-World, Long-Horizon Agent Evaluation

arXiv:2605.10912v1 Announce Type: new Abstract: Large language and vision-language models increasingly power agents that act on a user's behalf through command-line interface (CLI) harnesses. However,

AgentEscapeBench: Evaluating Out-of-Domain Tool-Grounded Reasoning in LLM Agents

arXiv:2605.07926v1 Announce Type: new Abstract: As LLM-based agents increasingly rely on external tools, it is important to evaluate their ability to sustain tool-grounded reasoning beyond familiar wo

Dual-Agent Co-Training for Health Coaching via Implicit Adversarial Preference Optimization

arXiv:2605.07011v1 Announce Type: new Abstract: Motivational-interviewing-based health coaching is an effective approach for improving mental health and promoting healthy behavior change. However, the

GraphDC: A Divide-and-Conquer Multi-Agent System for Scalable Graph Algorithm Reasoning

arXiv:2605.06671v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated strong potential for many mathematical problems. However, their performance on graph algorithmic tasks is

Hidden Coalitions in Multi-Agent AI: A Spectral Diagnostic from Internal Representations

arXiv:2605.06696v1 Announce Type: new Abstract: Collections of interacting AI agents can form coalitions, creating emergent group-level organization that is critical for AI safety and alignment. Howev

Learning Agent Routing From Early Experience

arXiv:2605.07180v1 Announce Type: new Abstract: LLM agents achieve strong performance on complex reasoning tasks but incur high latency and compute cost. In practice, many queries fall within the capa

MEMOREPAIR: Barrier-First Cascade Repair in Agentic Memory

arXiv:2605.07242v1 Announce Type: new Abstract: Agentic memory evolves across tasks into durable derived artifacts: summaries, cached outputs, embeddings, learned skills, and executable tool procedure

Securing Computer-Use Agents: A Unified Architecture-Lifecycle Framework for Deployment-Grounded Reliability

arXiv:2605.07110v1 Announce Type: new Abstract: Computer-use agents(CUAs)are moving frombounded benchmarks toward real software environments, wherethey operate browsers, desktops, mobile applications,

SREGym: A Live Benchmark for AI SRE Agents with High-Fidelity Failure Scenarios

arXiv:2605.07161v1 Announce Type: new Abstract: AI agents are increasingly used to diagnose and mitigate failures in production systems, known as agentic Site Reliability Engineering (SRE). Current SR

TeamBench: Evaluating Agent Coordination under Enforced Role Separation

arXiv:2605.07073v1 Announce Type: new Abstract: Agent systems often decompose a task across multiple roles, but these roles are typically specified by prompts rather than enforced by access controls.

VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents

arXiv:2506.21582v5 Announce Type: replace-cross Abstract: Text analytics has traditionally required specialized knowledge in Natural Language Processing (NLP) or text analysis, which presents a barrie

An Agent-Oriented Pluggable Experience-RAG Skill for Experience-Driven Retrieval Strategy Orchestration

arXiv:2605.03989v1 Announce Type: new Abstract: Retrieval-augmented generation systems often assume that one fixed retrieval pipeline is sufficient across heterogeneous tasks, yet factoid question ans

ARMATA: Auto-Regressive Multi-Agent Task Assignment

arXiv:2605.04225v1 Announce Type: cross Abstract: Coordinating multi-agent systems over spatially distributed areas requires solving a complex hierarchical problem: first distributing areas among agen

agentsarxiv-cs-ro

Learning to Orchestrate Agents in Natural Language with the Conductor

arXiv:2512.04388v5 Announce Type: replace Abstract: Powerful large language models (LLMs) from different providers have been expensively trained and finetuned to specialize across varying domains. In

LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey

arXiv:2505.00753v5 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have sparked growing interest in building fully autonomous agents. However, fully autonomous LLM-bas

safetyarxiv-cs-cl

Self-Induced Outcome Potential: Turn-Level Credit Assignment for Agents without Verifiers

arXiv:2605.04984v1 Announce Type: cross Abstract: Long-horizon LLM agents depend on intermediate information-gathering turns, yet training feedback is usually observed only at the final answer, becaus

Local Ai

An Empirical Study of Agent Skills for Healthcare: Practice, Gaps, and Governance

arXiv:2605.02709v1 Announce Type: new Abstract: Healthcare automation is shaped by local procedures and organizational constraints, so agent capabilities rarely transfer unchanged across settings. Age

local-aiarxiv-cs-ai

Intelligent Agents with Emotional Intelligence: Current Trends, Challenges, and Future Prospects

arXiv:2511.20657v2 Announce Type: replace-cross Abstract: The development of agents with emotional intelligence is becoming increasingly vital due to their significant role in human-computer interacti

Position: Safety and Fairness in Agentic AI Depend on Interaction Topology, Not on Model Scale or Alignment

arXiv:2605.01147v1 Announce Type: new Abstract: As large language models are increasingly deployed as interacting agents in high-stakes decisions, the AI safety community assumes that safety propertie

Runtime Evaluation of Procedural Content Generation in an Endless Runner Game Using Autonomous Agents

arXiv:2605.01783v1 Announce Type: new Abstract: Procedural Content Generation (PCG) enables game content to be created algorithmically without direct manual level-design effort, but it introduces a se

Truth or Tribe: How In-group Favoritism Prioritize Facts in Persona Agents

arXiv:2605.01329v1 Announce Type: new Abstract: In-group favoritism refers to the phenomena of favoring members of one's in-group over out-group members and is widely observed in numerous social coope

Workspace-Bench 1.0: Benchmarking AI Agents on Workspace Tasks with Large-Scale File Dependencies

arXiv:2605.03596v1 Announce Type: cross Abstract: Workspace learning requires AI agents to identify, reason over, exploit, and update explicit and implicit dependencies among heterogeneous files in a

A Language for Describing Agentic LLM Contexts

arXiv:2605.01920v1 Announce Type: cross Abstract: Large language models are increasingly used within larger systems ('LLM agents'). These make a sequence of LLM calls, each call providing the LLM with

TADI: Tool-Augmented Drilling Intelligence via Agentic LLM Orchestration over Heterogeneous Wellsite Data

arXiv:2605.00060v1 Announce Type: new Abstract: We present TADI (Tool-Augmented Drilling Intelligence), an agentic AI system that transforms drilling operational data into evidence-based analytical in

Watermarking LLM Agent Trajectories

arXiv:2602.18700v2 Announce Type: replace-cross Abstract: LLM agents rely heavily on high-quality trajectory data to guide their problem-solving behaviors, yet producing such data requires substantial

When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems

arXiv:2605.01133v1 Announce Type: cross Abstract: Large language model (LLM)-powered multi-agent systems (MAS) enable agents to communicate and share information, achieving strong performance on compl

safetyarxiv-cs-lg

Affordance Agent Harness: Verification-Gated Skill Orchestration

arXiv:2605.00663v1 Announce Type: cross Abstract: Affordance grounding requires identifying where and how an agent should interact in open-world scenes, where actionable regions are often small, occlu

agentsarxiv-cs-cv

Disentangled Control of Multi-Agent Systems

arXiv:2511.05900v3 Announce Type: replace-cross Abstract: This paper develops a general framework for multi-agent control synthesis, which applies to a wide range of problems with convergence guarante

agentsarxiv-cs-ro

Group Cognition Learning: Making Everything Better Through Governed Two-Stage Agents Collaboration

arXiv:2605.00370v1 Announce Type: new Abstract: Centralized multimodal learning commonly compresses language, acoustic, and visual signals into a single fused representation for prediction. While effe

Scaling Video Understanding via Compact Latent Multi-Agent Collaboration

arXiv:2605.00444v1 Announce Type: new Abstract: Multi-modal large language models (MLLMs) advance vision language understanding but face inherent limitations in long-video tasks due to bounded percept

safetyarxiv-cs-cv

Agentic Compilation: Mitigating the LLM Rerun Crisis for Minimized-Inference-Cost Web Automation

arXiv:2604.09718v2 Announce Type: cross Abstract: LLM-driven web agents operating through continuous inference loops -- repeatedly querying a model to evaluate browser state and select actions -- exhi

1 May 2026

AgenticRecTune: Multi-Agent with Self-Evolving Skillhub for Recommendation System Optimization

arXiv:2604.26969v1 Announce Type: cross Abstract: Modern large-scale recommendation systems are typically constructed as multi-stage pipelines, encompassing pre-ranking, ranking, and re-ranking phases