Search: “agents”

RemoteAgent: Bridging Vague Human Intents and Earth Observation with RL-based Agentic MLLMs

arXiv:2604.07765v1 Announce Type: new Abstract: Earth Observation (EO) systems are essentially designed to support domain experts who often express their requirements through vague natural language ra

agentsarxiv-cs-cv

10 Apr 2026

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Local Ai

Agent Skill Framework: Perspectives on the Potential of Small to Medium Language Models in Industrial Environments

DGX agent

arXiv:2602.16653v4 Announce Type: replace Abstract: Skills are getting increasingly used in recent agentic frameworks, performing robustly with proprietary LLMs. Yet, their effectiveness for small and

local-aiarxiv-cs-ai

16 Oct 2026

Mallea: Building, Steering, and Memorizing Worlds with Coding Agent

arXiv:2610.21283v1 Announce Type: new Abstract: Code world models represent world dynamics through explicit state and executable rules. We investigate how to coordinate object representations, behavio

16 Oct 2026

Matoi: Selective Revalidation of Consequence Evidence for Agent Authorization

arXiv:2610.21394v1 Announce Type: cross Abstract: Matoi separates reusable consequence evidence from current execution authority and durable occurrence history. Its finite query-aware contract covers

16 Oct 2026

X-RIC: An Agentic RAN-Intelligent Controller Benchmark for Enhancing Reinforcement Learning

arXiv:2610.22269v1 Announce Type: new Abstract: The O-RAN ALLIANCE introduces architectural flexibility through disaggregation and AI-driven control. While the RAN Intelligent Controller (RIC) enables

16 Oct 2026

Beyond the Verdict: Agentic Code Judging with Verifiable Feedback

arXiv:2610.18760v1 Announce Type: new Abstract: Test-time scaling for large language models (LLMs) can involve generating multiple candidate solutions for selection or revising an earlier attempt. To

Do Perturbation Predictors Learn Gene Interactions? Diagnosing Extrapolation in Agentic Screening

arXiv:2610.18880v1 Announce Type: new Abstract: High-throughput perturbation screens increasingly use machine-learning models to predict the effects of gene combinations that were never measured. A di

Learning Adaptive Deliberation Control for Reliable Recognition with Multi-Agent Language Models

arXiv:2610.17840v1 Announce Type: new Abstract: Multi-agent deliberation can improve recognition by criticizing and revising candidate answers, but fixed controls cannot respond to changes in disagree

Memory Echo in Single-Agent Long-Term Memory: Lifecycle Evaluation and Provenance-Guided Mitigation

arXiv:2610.17763v1 Announce Type: new Abstract: Long-term memory supports agents across sessions. Repeated retrieval and write-back can let one historical claim occupy multiple retrieval positions and

NePPO: Near-Potential Policy Optimization for General-Sum Multi-Agent Reinforcement Learning

arXiv:2603.06977v3 Announce Type: replace Abstract: Multi-agent reinforcement learning (MARL) is increasingly used to design learning-enabled agents that interact in shared environments. However, trai

ScholarQuest: A Taxonomy-Guided Benchmark for Agentic Academic Paper Search in Open Literature Environments

arXiv:2606.20235v2 Announce Type: replace-cross Abstract: Academic paper search is a core step in scientific research, and LLM-based search agents are emerging as a promising paradigm for iterative, i

Self-Evolving Agent Harness

arXiv:2610.18813v1 Announce Type: new Abstract: Harness self-evolution revises an agent's software scaffolding, including prompts, memory, workflows, and executable components, while keeping model wei

ThreadBench: Benchmarking Realism in Agentic Simulation of Real-world Discussions

arXiv:2606.14715v2 Announce Type: replace-cross Abstract: LLM agents are increasingly used to simulate real-world interactions, but it remains unclear whether simulated behaviors preserve the content

CB-Agent: Concept-Based In-Context Learning for Sequential Action Selection

model-releasesarxiv-cs-lg

arXiv:2610.14574v1 Announce Type: cross Abstract: In-context learning (ICL) allows large language models to use demonstrations without updating their parameters. For interactive agents, demonstrations

Davinci-Tool: Scaling Agentic Tool-Use Supervision with Verifiable Executable Environments

arXiv:2610.16867v1 Announce Type: new Abstract: Reliable agentic tool use requires training data that pair diverse multi-step workflows with executable evidence that the requested outcomes were achiev

Ensemble-MIX: Enhancing Sample-Efficiency in Multi-Agent RL via Selective Ensemble-Based Exploration

arXiv:2506.02841v5 Announce Type: replace-cross Abstract: Multi-agent reinforcement learning (MARL) methods have achieved state-of-the-art results on a range of multi-agent tasks. Yet, MARL algorithms

FRACTION: Fraud Explanation Generation via Agentic Graph Context Navigation

arXiv:2610.18023v1 Announce Type: new Abstract: Graph fraud explanation generation emerges as an important task, which requires jointly leveraging graph structure and content information to produce hu

SEEK: Agentic Knowledge Graph Retrieval for Secure Code Generation

arXiv:2610.14968v1 Announce Type: cross Abstract: Large Language Models (LLMs) can generate functionally correct code while introducing exploitable security weaknesses, particularly when developers sp

TopoCurate:Modeling Interaction Topology for Tool-Use Agent Training

arXiv:2603.01714v2 Announce Type: replace Abstract: Training tool-use agents typically relies on outcome-based filtering: Supervised Fine-Tuning (SFT) on successful trajectories and Reinforcement Lear

Towards Physically Grounded Articulated 3D Assets: A Multi-Agent Pipeline and Benchmark

model-releasesarxiv-cs-cv

arXiv:2610.13947v2 Announce Type: replace Abstract: In this paper, we study physically grounded articulated 3D asset generation---moving the goal from reproducing how objects look to capturing how the

Training-Free Multi-Agent Cooperative Embodied Search from Uncertain Vision-Language Priors

arXiv:2610.15038v1 Announce Type: new Abstract: Real-world Vision-Language Navigation (VLN) requires agents to act under partial observability, where map structure, semantic cues, and target locations

safetyarxiv-cs-ro

LongHarness: Advancing Agentic Reasoning over 100M-Token Corpora via Stateful Evidence Management

arXiv:2610.13075v1 Announce Type: new Abstract: Corpus-level long-context reasoning requires agents to acquire and integrate evidence across document collections that exceed their context windows. Exi

12 Oct 2026

Arbiter: Detecting Interference in LLM Agent System Prompts

arXiv:2603.08993v2 Announce Type: replace-cross Abstract: System prompts for LLM-based coding agents are software artifacts that govern agent behavior, yet lack the testing infrastructure applied to c

Constitutional Gating and Deterministic Recovery for Multi-Agent LLM Negotiation: Ablations Against a Stateful Adversarial Gatekeeper

arXiv:2610.11542v1 Announce Type: cross Abstract: Multi-agent LLM systems negotiating with a stateful counterpart waste model calls in three ways: polite loops that never meet the counterpart's hidden

Narrow and Deep: An Ontology Tower as the Knowledge of an LLM Agent for an Industrial Equipment System

arXiv:2610.11768v1 Announce Type: cross Abstract: Large language model (LLM) agents are beginning to operate industrial energy equipment, and what they get right depends on what they are told about th

Project Greenhouse: Progress Toward Fully Open and Sovereign Agentic Search

arXiv:2610.11922v1 Announce Type: cross Abstract: Project Greenhouse represents our exploration of a simple thesis: We believe that it is possible to build fully open and sovereign models for agentic

agentsarxiv-cs-cl

ReCast: Attribution-Oriented Step Representation Learning for LLM-Based Agent Systems

arXiv:2610.11334v1 Announce Type: new Abstract: In LLM-based agent systems, failures can originate from early steps whose effects propagate through subsequent interactions, making their origins diffic

Local Ai

Trajectory-Guided Fault Localization for Agent Skill Evolution

arXiv:2610.11858v1 Announce Type: cross Abstract: Agent skills provide reusable guidance for code agents, but incomplete or unsuitable guidance can impair task execution. To reduce the manual effort o

local-aiarxiv-cs-ai

An Empirical Study of Agent Skills' Downstream Utility

arXiv:2610.08875v1 Announce Type: cross Abstract: Agent Skills package procedural guidance and resources for reuse, but a relevant Skill does not necessarily improve task performance. Existing studies

CRT-HMAR: Causal Requirement Tracing-Guided Hierarchical Multi-Agent Regulation for Open-Task-Aware Infrared-Visible Image Fusion

arXiv:2610.09330v1 Announce Type: new Abstract: Infrared and visible (IR-VIS) image fusion integrates complementary multimodal information into a single fused image to support downstream vision tasks.

agentsarxiv-cs-cv

Shared-Roadmap Generation and Evaluator for Multi-Agent Path Planning Using Heterogeneous Graph Neural Network

arXiv:2610.09034v1 Announce Type: cross Abstract: Multi-agent path planning (MAPP) in continuous environments often relies on roadmaps to balance safety and search efficiency. However, traditional roa

Task-Oriented Key-Layer KV Communication for Efficient Latent Multi-Agent Collaboration

arXiv:2610.08820v1 Announce Type: new Abstract: Large language model-based multi-agent systems improve complex problem solving through collaboration, while latent communication directly transmits mode

Adapting to Changes in Agent Behavior via Finite-Depth Policy Sensitivity

model-releasesarxiv-cs-lg

arXiv:2610.07475v1 Announce Type: new Abstract: Adapting a reinforcement learning policy to changes in another agent's behavior typically requires a large amount of new interaction data. Policy sensit

7 Oct 2026

NeMo-DCR: Bit-Exact Delta-Compressed Refit for Scalable Agentic RL at Trillion-Parameter Scale

arXiv:2610.08430v1 Announce Type: cross Abstract: Agentic reinforcement learning (RL) disaggregates training from rollout, so each policy update must reach the rollout clusters before the next batch.

7 Oct 2026

Text2Dashboard: A Governed Agent Architecture for Natural-Language Dashboard Generation over Enterprise DataBrain

arXiv:2610.06914v1 Announce Type: new Abstract: Text2Dashboard is a DataBrain-specific prototype that turns natural-language analytic requests into inspectable dashboards. An installable Codex plugin

7 Oct 2026

From Social Reasoning to Embodied Interaction: An Agentic Framework for Social Robots

arXiv:2610.05964v1 Announce Type: new Abstract: Natural face-to-face human--robot interaction requires a robot to understand an evolving social situation, decide when to engage, and express its intent

agentsarxiv-cs-ro

G-CARB: Graph-Localized Conformal Agent Risk Budget for Compositional Harm

arXiv:2610.05563v1 Announce Type: cross Abstract: Small language model (SLM) agents need safety controls that track consequences across tool calls with little monitoring overhead. A private read, for

Local Ai

PreAct-Nav: Agentic Reasoning Before Action for Urban Navigation

arXiv:2610.04916v1 Announce Type: new Abstract: Urban navigation requires embodied agents to pursue long-horizon goals through local decisions based on egocentric observations. However, existing agent

local-aiarxiv-cs-ro

Selecting Long-Horizon Trajectories for Reliable and Efficient Terminal-Agent Training

arXiv:2610.05831v1 Announce Type: new Abstract: Terminal agents are commonly trained by imitating long teacher trajectories, yet how much of each trajectory to supervise remains unexplored. We study t

Threat-Preserving Representation Sensitivity in Agent-Security Benchmarks

arXiv:2610.03585v1 Announce Type: cross Abstract: Security benchmarks for LLM-based agents often report the attack success rate (ASR) as a measure of model robustness and use these scores to compare d

5 Oct 2026

AstroAgentBench: Evaluating Agentic Planning on Space Mission Planning Tasks

arXiv:2601.11354v2 Announce Type: replace Abstract: Recent LLM-for-Space systems address mission planning, scheduling, operations support, simulator control, and autonomy, but their evaluations use di

Fault-Tolerant Budget Conservation in Distributed Multi-Agent Delegation

arXiv:2610.00349v1 Announce Type: new Abstract: Resource limits are becoming an authorization boundary for AI agents that delegate work across concurrent and failure-prone workers. Parent-child alloca

JevSpawn: Adaptive Agentic Inference through Compositional Action Spaces

arXiv:2610.00437v1 Announce Type: new Abstract: LLM agents generate intermediate reasoning and actions token by token, making extended interactions slow and computationally expensive. Jev-style models

SHARPO: Segment-Level Credit Assignment for Agentic Reinforcement Learning

arXiv:2610.00838v1 Announce Type: cross Abstract: Agentic reinforcement learning (RL) trains a large language model (LLM) to act over long, multi-step interactions. However, a single localized error c

What Should an Agent Remember? Disentangling Retention from Retrieval in Bounded-Memory Evaluation

arXiv:2610.00366v1 Announce Type: new Abstract: A persistent agent must decide both what to retain as information arrives and what to surface once a query appears, yet memory evaluations can confound

Divide and Collapse: MAPF-Collapse via Exact Decomposition into Independent Sub-Instances

arXiv:2609.39559v1 Announce Type: new Abstract: In this work we study the problem of MAPFC, a post-optimization step for Multi-Agent Path Finding (MAPF) plans where we are given a feasible plan produc

1 Oct 2026

GraphCert: Bootstrap Agentic Graph Reasoning with Certified Evidence Rubrics

arXiv:2609.38798v1 Announce Type: new Abstract: Graph agents extend large language models (LLMs) with the ability to actively explore and reason over knowledge graphs through multi-step interactions w

1 Oct 2026

HARDE: Optimizing Agent Harnesses for Runtime Risk Detection and Execution Control