Search: “agents”

Similarity Gates Approve Reversals: A Validity Audit of Embedding-Cosine Thresholds in Agent Systems

arXiv:2608.10216v1 Announce Type: cross Abstract: Agent frameworks ship quality gates that compare text blocks by embedding-cosine similarity and decide at a fixed cutoff. Deduplication filters, seman

12 Aug 2026

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A Unified Issue Resolution Benchmark for Requirement Clarification, Planning, and Code Generation for Coding Agents

DGX agent

arXiv:2608.09072v1 Announce Type: cross Abstract: Large language model-powered coding agents are increasingly used to modify existing code repositories, for example, by adding features or fixing bugs.

model-releasesarxiv-cs-ai

11 Aug 2026

Agentic Auto-Research is Fuzz Testing

arXiv:2608.09855v1 Announce Type: new Abstract: Autonomous research agents can generate experiments faster than researchers can validate them. Researchers have responded by scaling the proposer and ra

Can Coding Agents Solve Repository-Level Issues with Rendered Code? An Exploratory Study of Visual Representations

arXiv:2608.09268v1 Announce Type: cross Abstract: Visual modality has recently been explored as a way to compress textual tokens, including rendering code as images for static code understanding. We s

CEAA: A Cognitive Embodied Agents Architecture for Interactive Computing Systems

arXiv:2608.09848v1 Announce Type: new Abstract: The development of embodied Intelligent Virtual Agents (IVAs) that have cognitive capabilities in real-time interactive virtual environments remains a c

Local Ai

ColluSkill: Adversarial Cross-Skill Composition for Evading Agent Skill Scanners

arXiv:2608.09732v1 Announce Type: cross Abstract: Agent skills are emerging as an important attack surface in LLM-based agent systems. Through an empirical study of existing skill scanners, we find th

local-aiarxiv-cs-ai

CommitKV: Lifecycle-Aware KV Cache Compression via Commit Transitions for Multi-Turn Agents

arXiv:2608.07855v1 Announce Type: new Abstract: Multi-turn Reasoning-and-Acting (ReAct) agents accumulate growing trajectories of reasoning, tool calls, and observations. Their key-value (KV) caches g

agentsarxiv-cs-lg

Controlled Memory Interference in Continual LLM Agents

arXiv:2608.07622v1 Announce Type: new Abstract: Long-term memory enables AI agents to maintain continuity across sessions, personalize behavior, and evolve through accumulated experience. Yet memory e

Improving Constraint Models with LLM Agents

arXiv:2608.08127v1 Announce Type: new Abstract: The runtime of Constraint Programming (CP) solvers is highly sensitive to modeling choices, such as symmetry breaking, implied constraints, global const

Learning from Environmental Feedback: Credit Assignment across Multiple Timescales for Agentic Reinforcement Learning

arXiv:2608.08255v1 Announce Type: cross Abstract: Agentic reinforcement learning (RL) often suffers from delayed and sparse rewards in real-world environments. A promising solution to this challenge i

agentsarxiv-cs-cl

M^3Prune: Hierarchical Communication Graph Pruning for Efficient Multi-Modal Multi-Agent Retrieval-Augmented Generation

arXiv:2511.19969v2 Announce Type: replace Abstract: Recent advancements in multi-modal retrieval-augmented generation (mRAG), which enhance multi-modal large language models (MLLMs) with external know

Not Worth Another Token: Marginal Value Estimation for Efficient Deep Research Agents

arXiv:2608.08389v1 Announce Type: new Abstract: Long-horizon research agents solve open-ended tasks through iterative retrieval, aggregation, and synthesis, but context grows rapidly while the margina

Reflex First, Reflect Later: Latency-Aware Embodied LLM Agents for Dynamic Response

arXiv:2506.07223v2 Announce Type: replace Abstract: Large language models (LLMs) have substantially improved the planning capabilities of embodied agents, enabling their deployment in dynamic and safe

SkillSentry: Reliable Skill Execution for LLM Agents via Runtime Assurance

arXiv:2608.09253v1 Announce Type: new Abstract: LLM agents are increasingly equipped with skills to perform complex tasks through multi-step reasoning and tool use. Although skills provide reusable pr

The Collaboration Gap: Exploration and Benchmarking of Open-World Agentic Cooperation

arXiv:2511.02687v2 Announce Type: replace Abstract: The trajectory of AI development suggests that we will increasingly rely on agent-based systems powered by language models, composed of independentl

The Scaffolding Matters More Than the Interface: A Controlled Comparison of MCP and CLI Tool Use Across Seven Agent Scaffoldings, Five Language Models, and One Software Task

arXiv:2608.08654v1 Announce Type: new Abstract: How much an AI coding agent costs to run can depend more on the agent scaffolding that drives it than on the interface through which it reaches its tool

Agentic Planning for Symbolic Execution

arXiv:2608.06397v1 Announce Type: cross Abstract: Symbolic execution seeks to explore feasible program paths, yet a practical run may exhaust its resources while much program behaviour remains unreach

Evaluating XAI Support From A Hierarchical Reinforcement Learning Policy in Human-Agent Collaboration

arXiv:2608.06381v1 Announce Type: cross Abstract: Explainable AI (XAI) has shown promise for human-agent collaboration, yet results rely on hand-crafted policies in custom environments, limiting gener

Long-Horizon Agent Trajectory Attribution: A Unified Benchmark and Fine-Grained Annotation Framework

arXiv:2608.06909v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate through long-horizon trajectories involving user instructions, tool use, external observations, a

Local Ai

Online Monitoring and Corrective Steering of Programming Agents

arXiv:2608.06701v1 Announce Type: cross Abstract: Fixing GitHub issues in large-scale projects is a long-horizon task, especially when a fix requires changes across multiple locations or the issue des

local-aiarxiv-cs-ai

AV-AIVAT: 74x Cheaper Agent Evaluation with Certified Anytime-Valid Stopping in Imperfect-Information Games

arXiv:2608.06362v1 Announce Type: cross Abstract: Deciding which of two agents is stronger means playing games until skill outweighs luck, and every game costs money, model inference, or expert time.

7 Aug 2026

Breadcrumbing Search Agents

arXiv:2608.04565v1 Announce Type: cross Abstract: LLM-based search agents are widely used for information-seeking tasks, but their reliance on external tool returns introduces a critical security risk

DAC-Pose: Dual-Agent Collaborative Framework for Pose-Guided Human Generation

arXiv:2608.04622v1 Announce Type: new Abstract: AI agents have emerged as a powerful new paradigm in generative image synthesis, enabling systems to perform complex semantic reasoning rather than pass

safetyarxiv-cs-cv

EviGraph: Evidence-Guided Autonomous Research Agents

arXiv:2608.04738v1 Announce Type: new Abstract: Autonomous research agents can generate hypotheses, execute experiments, and draft manuscripts, yet their outputs often contain unsupported claims and i

MatrAIx: Simulating the World with 8.3 Billion Persona Agents

arXiv:2608.04205v1 Announce Type: new Abstract: Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract aw

OneDayAgent: Towards a Long-Horizon Harness for Autonomous Agents

arXiv:2608.05013v1 Announce Type: cross Abstract: LLM agents are increasingly applied to open-ended everyday requests that span work, study, and life. These tasks are long-horizon, cross-environment,

PRIMAL3: Pathfinding via Reinforcement and Imitation Multi-Agent Learning - Leveraging LaCAM3

arXiv:2608.04905v1 Announce Type: new Abstract: We present PRIMAL3, an ultra-large-scale learning-based framework for multi-agent pathfinding (MAPF) that integrates reinforcement learning, topology-aw

safetyarxiv-cs-ro

GDPevo: Evaluating Agent Self-Evolution on Real Business Tasks

arXiv:2608.03764v1 Announce Type: new Abstract: Agent self-evolution updates an agent's persistent state from prior experience and reuses it to solve related tasks more effectively. Evaluating self-ev

Improving Sample Efficiency in Multi-Agent Reinforcement Learning for Simulated Football Games via Exploration

arXiv:2503.13077v2 Announce Type: replace Abstract: Multi-agent reinforcement learning has shown promise in learning cooperative behaviors in team-based environments. However, such methods often deman

agentsarxiv-cs-lg

OR-Agent: Bridging Evolutionary Search and Structured Research for Automated Algorithm Discovery

arXiv:2602.13769v3 Announce Type: replace Abstract: Automating heuristic design in complex, experiment-driven domains requires more than iterative mutation of solution algorithms. Current LLM-based ev

Search, Inspect, Fetch: Exploiting Boolean Retrieval for Deep-Research Agents

arXiv:2608.02751v1 Announce Type: cross Abstract: Existing deep-research agents use a search-visit workflow that retrieves and reads whole pages, without considering the addressable structure that web

Training Documents Reranker with Search Rubrics for Deep Research Agent

arXiv:2608.03527v1 Announce Type: cross Abstract: Retrieval systems help deep research agents generate high-quality answers by providing relevant documents. However, existing retrievers typically sele

Where Did It Go Wrong? Process-Level Evaluation of Web Agents with Semantic State Tracking

arXiv:2606.15673v2 Announce Type: replace Abstract: Web agents act through long interaction sequences, yet existing benchmarks evaluate only terminal success, discarding all process information and of

AgentMemBench: A Systematic Benchmark for Evaluating Long-Term Memory Management Strategies in Conversational AI Agents

model-releasesarxiv-cs-cl

arXiv:2608.00009v1 Announce Type: new Abstract: Long-term memory remains a critical bottleneck for conversational AI agents, whose finite context windows cannot support coherent recall across thousand

DrawAI: Agentic Benchmark and Workflow for Making Raster Images Editable

model-releasesarxiv-cs-cv

arXiv:2608.00548v1 Announce Type: new Abstract: Recent image-generation models and multimodal agents can produce high-quality visuals for increasingly complex visual communication tasks. Yet their ras

PGMem: Tightly Coupled Persona-Memory Graph for Lifelong Personalized Agents

arXiv:2608.01708v1 Announce Type: new Abstract: Long-term personalized dialogue agents must track user preferences as their personas evolve. Existing memory systems organize past events well, but stor

agentsarxiv-cs-cl

Token-Native Storage: Read and Write in your Agent's Language

arXiv:2608.02376v1 Announce Type: cross Abstract: Search and database engines still store text as UTF-8, a format built for humans. But the systems that increasingly read and write that text (embedder

agentsarxiv-cs-cl

Trajectories That Segment Themselves: Agent-Declared Boundaries as a Training Unit

arXiv:2608.02302v1 Announce Type: cross Abstract: Long-horizon coding-agent trajectories are poorly matched to the credit units available to train on: a single action has no stable value, an episode l

agentsarxiv-cs-lg

AMTFV: Agentic Mathematical Tool-Flow Verification for LLM Self-Correction

arXiv:2607.29549v1 Announce Type: new Abstract: Large language models have demonstrated strong mathematical problem-solving capabilities, yet reliably verifying their candidate answers remains challen

EduPanel: A Three-Agent LLM Judge for Teaching Videos -- Reliability, Complementarity, and Human Trust Calibration

arXiv:2607.18529v2 Announce Type: replace-cross Abstract: Teaching videos are becoming a major medium for education, creating a growing need for scalable evaluation of their pedagogical quality. Exist

Local Ai

RecHarness: A Bandit-Routed Agentic Harness for Self-Evolving Recommender Systems

arXiv:2607.29241v1 Announce Type: cross Abstract: Optimizing modern recommender models still depends heavily on engineers manually iterating over architectural, objective, and training-strategy change

local-aiarxiv-cs-ai

SciToolAgent-Evo: An Ontology-Aware Self-Evolving Agent for Open-World Scientific Tool Acquisition

arXiv:2607.28692v1 Announce Type: new Abstract: Large language model (LLM) agents have been increasingly adopted in scientific research for organizing and invoking specialized computational tools. How

Tool Specifications Matter: Uncovering and Mitigating Safety Risks in AI Agents

arXiv:2607.29254v1 Announce Type: new Abstract: AI agents extend large language models (LLMs) with external tools, enabling them to perform complex tasks and translate model outputs into consequential

Validation Evidence in LLM Repair Agents: How Much of What Passes Actually Tests the Bug?

arXiv:2607.28871v1 Announce Type: cross Abstract: When a repair agent runs a test and sees it pass, the result is treated as evidence about the reported defect. We measure how often that treatment is

A Graph-Native Bitemporal Memory Store for Conversational AI Agents

arXiv:2607.26520v1 Announce Type: cross Abstract: Conversational AI agents commonly lack persistent memory across sessions. The obvious fixes like injecting full chat histories into the context window

ClinLens: Towards Long-Horizon Coding Agents for Longitudinal Multimodal Clinical Data Science

arXiv:2607.26155v1 Announce Type: new Abstract: Clinical data-science agents must transform heterogeneous longitudinal records into auditable analyses, yet existing benchmarks largely isolate medical

Echoverse: Deep, Evolving Environments for Training Computer-Use Agents at Scale

model-releasesarxiv-cs-lg

arXiv:2607.28074v1 Announce Type: cross Abstract: Computer-use agents learn from what their actions change, so training one needs applications it can act on, break and reset. The applications that mat

IDP AutoOpt: Agent-Driven Optimization of Document Processing Pipeline Configurations

arXiv:2607.26075v1 Announce Type: cross Abstract: We present IDP AutoOpt, an autonomous LLM agent that discovers high-performing configurations for intelligent document processing (IDP) pipelines. Tun