Search: “agents”

Probing the Knowledge Boundary: An Interactive Agentic Framework for Deep Knowledge Extraction

arXiv:2602.00959v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) can be seen as compressed knowledge bases, but it remains unclear what knowledge they truly contain and how far t

agentsarxiv-cs-cl

27 May 2026

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StepOPSD: Step-Aware Online Preference Distillation for Agent Reinforcement Learning

DGX agent

arXiv:2605.27140v1 Announce Type: new Abstract: Reinforcement learning for multi-turn agents suffers from a credit-assignment mismatch: rewards are sparse and trajectory-level, while success often hin

safetyarxiv-cs-ai

27 May 2026

A Multi-Agent LLM Framework for Rating the Quality of Surgical Feedback

arXiv:2605.25440v1 Announce Type: cross Abstract: Verbal feedback delivered by attending surgeons in the operating room plays a critical formative role in resident trainee skill acquisition. Yet, asse

Can LLMs Time Travel? Enhancing Temporal Consistency in Legal Agentic Search through Reinforcement Learning

arXiv:2605.25920v1 Announce Type: cross Abstract: While large language models (LLMs) augmented with agentic search capabilities show promise for legal reasoning, they overlook a fundamental constraint

Hide-and-Shill: A Reinforcement Learning Framework for Market Manipulation Detection in Symphony-a Decentralized Multi-Agent System

arXiv:2507.09179v3 Announce Type: replace Abstract: Decentralized finance (DeFi) has introduced a new era of permissionless financial innovation but also led to unprecedented market manipulation. With

MimirRAG: A Multi-Agent RAG Framework for Financial Data Retrieval with Metadata Integration

model-releasesarxiv-cs-lg

arXiv:2605.25030v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems offer a promising approach to reduce hallucinations and improve answer accuracy in large language models (L

PolyGnosis 2.0: Enhancing LLM Reasoning via Agentic Harness Engineering for Polymarket and OSINT Insight Extraction

arXiv:2605.25958v1 Announce Type: new Abstract: This paper introduces PolyGnosis 2.0, a pioneering multi-agent architecture designed to extract predictive intelligence by synthesizing Polymarket anoma

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Understanding Conversational Patterns in Multi-agent Programming: A Case Study on Fibonacci Game Development

arXiv:2605.24138v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly applied to software engineering (SE), yet their potential for autonomous, role-oriented collaboration re

Agentic-VLA: Efficient Online Adaptation for Vision-Language-Action Models

arXiv:2605.22896v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for robotic manipulation by leveraging pre-trained vision-language representa

Energy per Successful Goal: Goal-Level Energy Accounting for Agentic AI Systems

arXiv:2605.22883v1 Announce Type: new Abstract: Current AI energy benchmarks measure consumption at the granularity of a single model invocation or training run. For classical single-turn workloads th

KPI2KVI: A Multi Agent Workflow for Calculating Key Value Indicators from Service Descriptions

arXiv:2605.22825v1 Announce Type: cross Abstract: Key Value Indicators (KVIs) provide a decision oriented view of a service by summarizing how operational performance translates into stakeholder value

NeuroWeaver: An Autonomous Evolutionary Agent for Exploring the Programmatic Space of EEG Analysis Pipelines

arXiv:2602.13473v2 Announce Type: replace Abstract: Although foundation models have demonstrated remarkable success in general domains, the application of these models to electroencephalography (EEG)

SafeHarbor: Hierarchical Memory-Augmented Guardrail for LLM Agent Safety

arXiv:2605.05704v2 Announce Type: replace-cross Abstract: Recent advances in foundation models have transformed LLMs from passive conversational systems into autonomous agents capable of reasoning and

Governance by Design: Architecting Agentic AI for Organizational Learning and Scalable Autonomy

arXiv:2605.20210v1 Announce Type: cross Abstract: Agentic AI systems - systems that can pursue goals through multi-step planning and tool-mediated action with limited direct supervision - are moving f

ImProver: Agent-Based Automated Proof Optimization

arXiv:2410.04753v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have been used to generate formal proofs of mathematical theorems in proofs assistants such as Lean. However, we

agentsarxiv-cs-cl

RealUserSim: Bridging the Reality Gap in Agent Benchmarking via Grounded User Simulation

arXiv:2605.20204v1 Announce Type: cross Abstract: LLM-based user simulation is the primary mechanism for end-to-end agent evaluation, yet simulated users are poor proxies for real humans: unconstraine

STRUCTSENSE: A Task-Agnostic Agentic Framework for Structured Information Extraction with Human-In-The-Loop Evaluation and Benchmarking

arXiv:2507.03674v3 Announce Type: replace Abstract: Extracting structured information from scientific literature is critical for accelerating discovery, yet Large Language Models (LLMs) often struggle

agentsarxiv-cs-cl

X-OmniClaw Technical Report: A Unified Mobile Agent for Multimodal Understanding and Interaction

arXiv:2605.05765v2 Announce Type: replace Abstract: Inspired by the development of OpenClaw, there is a growing demand for mobile-based personal agents capable of handling complex and intuitive intera

safetyarxiv-cs-cv

Evolutionary Generation of Multi-Agent Systems

model-releasesarxiv-cs-lg

arXiv:2602.06511v3 Announce Type: replace Abstract: Large language model (LLM)-based multi-agent systems (MAS) show strong promise for complex reasoning, planning, and tool-augmented tasks, but design

21 May 2026

A Closed-loop, State-centric, Multi-agent Framework for Passenger Load Estimation from Heterogeneous Data Streams

arXiv:2605.19834v1 Announce Type: cross Abstract: To support operations and passenger-facing services, transit agencies need reliable passenger load trajectories. Currently, load estimates are typical

A novel YOLO26-MoE optimized by an LLM agent for insulator fault detection considering UAV images

arXiv:2605.19595v1 Announce Type: cross Abstract: The inspection of electrical power line insulators is essential for ensuring grid reliability and preventing failures caused by damaged or degraded in

Agentic Discovery of Cryomicroneedle Formulations

arXiv:2605.19677v1 Announce Type: new Abstract: Cryomicroneedles offer a route to minimally invasive intradermal delivery of living cells, but their cryogenic formulations must reconcile cell protecti

CMAD: Cooperative Multi-Agent Diffusion via Stochastic Optimal Control

arXiv:2602.10933v2 Announce Type: replace Abstract: Continuous-time generative models have achieved remarkable success in image restoration and synthesis. However, controlling the composition of multi

Towards Discovery of Polymers for Insulin Delivery via Physics-Grounded Agentic Workflows

arXiv:2605.18831v1 Announce Type: cross Abstract: Cold-chain storage limits access to insulin for hundreds of millions of people; a thermally protective patch polymer could help, but the design space

Agentic Cost-Aware Query Planning with Knowledge Distillation for Big Data Analytics

arXiv:2605.17831v1 Announce Type: new Abstract: Query optimization in big data analytics remains computationally expensive, particularly for resource-constrained environments where traditional optimiz

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory

arXiv:2511.20857v2 Announce Type: replace-cross Abstract: Statefulness is essential for large language model (LLM) agents to perform long-term planning and problem-solving. This makes memory a critica

Helping Customers in Distress: An LLM-powered Agent that Converses, Probes, and Routes

arXiv:2605.16268v1 Announce Type: cross Abstract: Banks receive millions of reports of fraud, scams, and disputed transactions every year, making it challenging to accurately direct customers to the a

KISS - Knowledge Infrastructure for Scientific Simulation: A Scaffolding for Agentic Earth Science

arXiv:2605.17856v1 Announce Type: new Abstract: Process-based simulation models encode decades of scientific understanding across the Earth sciences, yet the communities most exposed to climate risk a

LongMINT: Evaluating Memory under Multi-Target Interference in Long-Horizon Agent Systems

arXiv:2605.18565v1 Announce Type: cross Abstract: Real-world agents operate over long and evolving horizons, where information is repeatedly updated and may interfere across memories, requiring accura

PROTEA: Offline Evaluation and Iterative Refinement for Multi-Agent LLM Workflows

arXiv:2605.18032v1 Announce Type: cross Abstract: Multi-agent LLM workflows -- systems composed of multiple role-specific LLM calls -- often outperform single-prompt baselines, but they remain difficu

local-aiarxiv-cs-ai

R2V Agent: Teaching SLMs When to Ask for Help

arXiv:2605.16604v1 Announce Type: new Abstract: Efficient agentic systems should incur expensive frontier-model costs only on decisions where a cheaper local model is likely to fail. Existing LLM casc

local-aiarxiv-cs-lg

STRIDE: A Self-Reflective Agent Framework for Reliable Automatic Equation Discovery

arXiv:2605.17790v1 Announce Type: new Abstract: LLM-based equation discovery offers a promising route to recovering symbolic laws from data, but many systems still rely on generation-centered loops th

Verify-Gated Completion as Admission Control in a Governed Multi-Agent Runtime: A Bounded Architecture Case Study

arXiv:2605.17998v1 Announce Type: cross Abstract: As multi-agent systems move from short interactions to tool-using workflows with specialized roles and persistent state, completion becomes a runtime-

Agent4POI: Agentic Context-Conditioned Affordance Reasoning for Multimodal Point-of-Interest Recommendation

arXiv:2605.15203v1 Announce Type: cross Abstract: We introduce Agent4POI, the first POI recommendation framework that generates context-conditioned multimodal representations at recommendation time, r

AstraFlow: Dataflow-Oriented Reinforcement Learning for Agentic LLMs

arXiv:2605.15565v1 Announce Type: cross Abstract: Reinforcement learning (RL) is increasingly used to improve the reasoning, coding, and tool-use capabilities of large language models, but agentic RL

FORGE: Self-Evolving Agent Memory With No Weight Updates via Population Broadcast

arXiv:2605.16233v1 Announce Type: new Abstract: Can LLM agents improve decision-making through self-generated memory without gradient updates? We propose FORGE (Failure-Optimized Reflective Graduation

SkillSmith: Compiling Agent Skills into Boundary-Guided Runtime Interfaces

arXiv:2605.15215v1 Announce Type: new Abstract: Recently, skills have been widely adopted in large language model (LLM)-based agent systems across various domains. In existing frameworks, skills are t

UniShield: An Adaptive Multi-Agent Framework for Unified Forgery Image Detection and Localization

arXiv:2510.03161v2 Announce Type: replace-cross Abstract: With the rapid advancements in image generation, synthetic images have become increasingly realistic, posing significant societal risks, such

local-aiarxiv-cs-ai

A Tutorial on Cognitive Biases in Agentic AI-Driven 6G Autonomous Networks

arXiv:2510.19973v4 Announce Type: replace-cross Abstract: The path to higher network autonomy in 6G lies beyond the mere optimization of key performance indicators (KPIs), requiring systems that perce

Agentic Recommender System with Hierarchical Belief-State Memory

arXiv:2605.14401v1 Announce Type: cross Abstract: Memory-augmented LLM agents have advanced personalized recommendation, yet existing approaches universally adopt flat memory representations that conf

GroupMemBench: Benchmarking LLM Agent Memory in Multi-Party Conversations

model-releasesarxiv-cs-cl

arXiv:2605.14498v1 Announce Type: new Abstract: Large Language Model (LLM) agents increasingly serve as personal assistants and workplace collaborators, where their utility depends on memory systems t

Hypergraph Enterprise Agentic Reasoner over Heterogeneous Business Systems

arXiv:2605.14259v1 Announce Type: new Abstract: Applying Large Language Models (LLMs) to heterogeneous enterprise systems is hindered by hallucinations and failures in multi-hop, n-ary reasoning. Exis

LEMON: Learning Executable Multi-Agent Orchestration via Counterfactual Reinforcement Learning

arXiv:2605.14483v1 Announce Type: new Abstract: Large language models (LLMs) have become a strong foundation for multi-agent systems, but their effectiveness depends heavily on orchestration design. A

local-aiarxiv-cs-ai

MAPLE: Latent Multi-Agent Play for End-to-End Autonomous Driving

arXiv:2605.14201v1 Announce Type: cross Abstract: Vision-language-action (VLA) models are effective as end-to-end motion planners, but can be brittle when evaluated in closed-loop settings due to bein

safetyarxiv-cs-cv

Self-Distilled Agentic Reinforcement Learning

arXiv:2605.15155v1 Announce Type: cross Abstract: Reinforcement learning (RL) has emerged as a central paradigm for post-training LLM agents, yet its trajectory-level reward signal provides only coars

MARLIN: Multi-Agent Game-Theoretic Reinforcement Learning for Sustainable LLM Inference in Cloud Datacenters

arXiv:2605.13496v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become increasingly prevalent in cloud-based platforms, propelled by the introduction of AI-based consumer and enter

14 May 2026

Mechanism Plausibility in Generative Agent-Based Modeling

arXiv:2605.12824v1 Announce Type: cross Abstract: Large language models (LLMs) can generate high-level diverse phenomena without explicitly programmed rules. This capability has led to their adoption

14 May 2026

Multi-Dimensional Behavioral Evaluation of Agentic Stock Prediction Systems Using Large Language Model Judges with Closed-Loop Reinforcement Learning Feedback

arXiv:2605.05739v2 Announce Type: replace-cross Abstract: Forecast evaluation in finance has relied on aggregate accuracy metrics and predictive-accuracy tests built on point-forecast errors. These in