Search: “agents”

Artifacts as Memory Beyond the Agent Boundary

arXiv:2604.08756v1 Announce Type: new Abstract: The situated view of cognition holds that intelligent behavior depends not only on internal memory, but on an agent's active use of environmental resour

13 Apr 2026

Automated Standardization of Legacy Biomedical Metadata Using an Ontology-Constrained LLM Agent

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DGX agent

arXiv:2604.08552v1 Announce Type: cross Abstract: Scientific metadata are often incomplete and noncompliant with community standards, limiting dataset findability, interoperability, and reuse. When re

agentsarxiv-cs-ai

13 Apr 2026

Equivariant Multi-agent Reinforcement Learning for Multimodal Vehicle-to-Infrastructure Systems

arXiv:2604.06914v1 Announce Type: new Abstract: In this paper, we study a vehicle-to-infrastructure (V2I) system where distributed base stations (BSs) acting as road-side units (RSUs) collect multimod

safetyarxiv-cs-lg

10 Apr 2026

SkillTrojan: Backdoor Attacks on Skill-Based Agent Systems

arXiv:2604.06811v1 Announce Type: cross Abstract: Skill-based agent systems tackle complex tasks by composing reusable skills, improving modularity and scalability while introducing a largely unexamin

10 Apr 2026

AgentPerturb: Evaluating LLM Agent Robustness under Controlled Interaction Perturbations

arXiv:2610.21624v1 Announce Type: new Abstract: Real-world tasks are often complex and noisy, posing substantial challenges for LLM agents. Yet existing evaluations lack a systematic framework for joi

Constrained Multi-Agent Reinforcement Learning in Imagination

arXiv:2610.21319v1 Announce Type: new Abstract: Predicting cost in a multi-agent world model moves most constrained policy updates into imagination: the stronger model-free baseline needs 10 to 20 tim

DeSpatial: The devil of Agentic Spatial Reasoning Lies in 3D Itself

arXiv:2610.20990v1 Announce Type: new Abstract: Spatial agents have access to reconstruction and segmentation tools, yet inconsistent predictions and fragmented object identities can prevent their out

agentsarxiv-cs-cv

Diviner: Agentic RCA with Human-Governed Adaptation for Large-Scale Infrastructure

arXiv:2610.21281v1 Announce Type: new Abstract: Root-cause analysis (RCA) in large-scale distributed systems is challenging because a single symptom can cross service, data, configuration, compute, an

DocPilot: Interactive Agent Orchestration and Training for Long Visual Document Understanding

arXiv:2610.21327v1 Announce Type: new Abstract: Multimodal long-document question answering requires models to seek sparse evidence across pages and modalities, understand heterogeneous document conte

PriorityFEC: Deadline-Aware Streaming FEC for KV-Cache Handoff in Edge Multi-Agent Systems

arXiv:2610.21390v1 Announce Type: cross Abstract: Multi-agent large language model (LLM) systems are increasingly deployed at the edge to support complex tasks that require collaboration and informati

Probe-and-Resume: When and How to Evaluate Agent Execution

arXiv:2610.21088v1 Announce Type: new Abstract: Test-time search can improve agent performance by exploring alternative actions and using a critic to select promising branches. We study this approach

ReviewPilot: A Multi-Agent System for Screening and Data Extraction in Systematic Reviews

arXiv:2610.21042v1 Announce Type: cross Abstract: Systematic literature reviews follow the PRISMA process of screening scholarly works and extracting evidence from included studies. Deep research tool

WorkflowPerturb: Calibrated Stress Tests for Evaluating Multi-Agent Workflow Metrics

arXiv:2602.17990v4 Announce Type: replace Abstract: Multi-agent LLM systems that generate structured workflows from natural-language requests are now deployed in production across cloud automation, De

ANCHOR: Assessing Naturalistic Constraint Hierarchies and Ordering in Repository-Grounded Agentic Coding

model-releasesarxiv-cs-cl

arXiv:2610.16859v2 Announce Type: replace Abstract: For repository-grounded coding agents, a functionally correct patch is not necessarily an acceptable one: developers also constrain how the task mus

CockpitHAT: Dependency-Graph-Driven Hierarchical Attribution for Embodied Multi-Agent Cockpits

arXiv:2608.01805v2 Announce Type: replace Abstract: LLM multi-agent systems suffer from Correctness Collapse, where high task-level accuracy conceals severe process-level failures. This is especially

MolHop: Scaffold-Hopping Molecular Design with Agentic Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2610.19920v1 Announce Type: cross Abstract: Molecular design is often formulated as an optimization problem over existing molecular spaces. However, molecular optimization and the discovery of s

Output Discipline Sets the Floor: A Falsification-Guided, Model-Agnostic Agent Protocol for Auditable Hypothesis-Driven Decision Making

arXiv:2610.18298v1 Announce Type: new Abstract: What binds large language models on auditable, hypothesis-driven decision tasks, where every candidate can be checked against the evidence? On the publi

Risky-Bench: Evaluating Agentic Safety Risks in Real-World Life-Assist Deployments

arXiv:2602.03100v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly deployed as agents that operate in real-world environments, introducing safety risks beyond linguistic

Local Ai

SchemaWeaver: Accelerating On-Device Mobile Agentic AI via Schema-Guided Parallel LLM Decoding

arXiv:2610.17436v1 Announce Type: new Abstract: Large language models (LLMs) on mobile devices can act as agents that call external software tools to complete complex tasks, but the major challenge of

local-aiarxiv-cs-ai

Think in Strategies, Act with Tools: Traceable Agentic Optimization for Combinatorial Problems

arXiv:2610.14736v1 Announce Type: new Abstract: Optimization by PROmpting (OPRO) directly leverages Large Language Models (LLMs) to generate candidate solutions through natural-language prompting. How

VQEL: Enabling Self-Play in Emergent Language Games via Agent-Internal Vector Quantization

arXiv:2503.04940v3 Announce Type: replace-cross Abstract: Emergent Language (EL) focuses on the emergence of communication among artificial agents. Although symbolic communication channels more closel

AutoNovo: Agentic Program Search Discovers Transferable Nucleic Acid Design Algorithms

arXiv:2610.16232v1 Announce Type: new Abstract: In-silico optimization of nucleic acids relies on predictive oracles that imperfectly capture biological function, so sequences optimized against one mo

agentsarxiv-cs-lg

14 Oct 2026

Observe, Share, or Predict? Disentangling Partner Information in Embodied Multi-Agent Collaboration

model-releasesarxiv-cs-ro

arXiv:2610.16895v1 Announce Type: cross Abstract: LLMs are used as high-level controllers for embodied agents, but it remains unclear whether they support collaborative reasoning, such as anticipating

14 Oct 2026

VideoEvoHarness: Self Evolving Agent Harness from Unlabeled Videos for Video Understanding

model-releasesarxiv-cs-cv

arXiv:2610.15389v1 Announce Type: new Abstract: Video understanding agents rely on a harness to acquire evidence, use tools, and reason, but improving it requires substantial effort. Recent self evolu

14 Oct 2026

Rollout-Time Intervention: Unlocking Agentic Reinforcement Learning Beyond Policy Limits

arXiv:2610.13438v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as a key paradigm for improving large language model (LLM) agents, enabling stronger reasoning, planning, and to

12 Oct 2026

iAm.md: Robot Skill Self-Assessment through Agentic Introspection for Unknown Open-Vocabulary Domains

arXiv:2610.10962v1 Announce Type: cross Abstract: Agentic AI based on Large Language Model generalization capabilities offers a wide range of potential applications, including planning for embodied ta

OA-MAP: Evidence-Grounded Multi-Agent Multimodal Framework for Interpretable Knee Osteoarthritis Progression

arXiv:2610.12134v1 Announce Type: new Abstract: Knee osteoarthritis (KOA) progression prediction can support patient monitoring, requiring the integration of multimodal data and multidomain expertise.

OnTrack: Real-Time Monitoring and Intervention in LLM Agent Trajectories via Streaming Structure-Aware Optimal Transport

arXiv:2610.12375v1 Announce Type: new Abstract: Agents are deployed in applications from trip planners and stock trading to IT incident triage. In most cases, LLM agents work autonomously with minimal

SynCo: Data Synthesis Co-Training for Self-Evolving LLMs via Multi-Agent Reinforcement Learning

arXiv:2610.11345v1 Announce Type: new Abstract: Self-evolving LLM agents promise to improve autonomously through continual interaction and learning, reducing their dependence on manually curated super

CuratorMAS: Automating Dataset Curation via Multi-Agent Orchestration

arXiv:2610.07075v1 Announce Type: new Abstract: High-quality datasets are essential for reliable machine learning, but dataset curation remains costly and hard to generalize across domains. Existing m

How Much Evidence Should a Coding Agent's Self-Correction Carry? Adaptive Dirichlet Evidence for Self-Distillation

arXiv:2610.08514v1 Announce Type: new Abstract: Execution feedback lets coding agents revise programs and learn from their own corrections. A correction's learning weight should reflect both the trans

PsyCIDRA: A Dual-Agent Framework for Psychiatric Interviewing and Diagnostic Reasoning

arXiv:2610.07473v1 Announce Type: new Abstract: Large language models show promise in clinical reasoning, but psychiatric interviewing requires guiding an evolving conversation. Their ability to carry

RadOnc-Agent: An LLM-Orchestrated Framework for AI Workflows Across the Radiotherapy Care Pathway

arXiv:2610.06923v1 Announce Type: new Abstract: Artificial intelligence has advanced individual radiotherapy tasks, yet these capabilities remain separated across clinical stages, software environment

The Right Memory in the Wrong Context: Verifying Retrieval Admissibility in Long-Term Agent Memory

arXiv:2610.07309v1 Announce Type: new Abstract: Long-term-memory agents can retrieve relevant information that is inadmissible for the current request because it belongs to another principal, violates

APOD: reasoning-guided agentic population ordinary differential equation discovery for pharmacological digital twins

arXiv:2610.06227v1 Announce Type: cross Abstract: Establishing ordinary differential equations (ODEs) describing population data is a fundamental part of mathematical modeling in pharmacology, crucial

agentsarxiv-cs-lg

6 Oct 2026

SkillScriptBench: Benchmarking Self-Evolution of Executable Agent Skill Packages Beyond Markdown

model-releasesarxiv-cs-lg

arXiv:2610.04008v1 Announce Type: cross Abstract: Executable Agent Skills combine natural-language instructions and scripts into reusable packages for LLM agents, and revising them requires fixing err

6 Oct 2026

APDMem: Agent-Controlled Progressive Disclosure for Query-Adaptive Long-Term Memory

arXiv:2610.02472v1 Announce Type: cross Abstract: Personalized LLM assistants must recover sparse evidence from long conversation histories across queries of varying complexity. We introduce APDMem (A

5 Oct 2026

HASTE: Evolving Agent Harnesses Against Emerging Attacks Using Sparse Evidence

arXiv:2610.02920v1 Announce Type: new Abstract: Agent harnesses play a critical role in defenses by enforcing safety constraints to prevent unsafe actions. However, rapidly emerging attacks outpace ma

5 Oct 2026

Peer Influence across Heterogeneous AI Models

arXiv:2610.03095v1 Announce Type: new Abstract: When two AI agents disagree, who persuades whom? As multi-agent systems increasingly combine language models of different families and sizes, the answer

5 Oct 2026

Finding the Right Fit: Model-Harness Interactions across Agent Tasks

arXiv:2610.00917v1 Announce Type: new Abstract: Choosing an agent system means choosing both a language model and the harness through which it acts. We ask whether a strong model, harness, or pairing

2 Oct 2026

MCRI: A Four-Dimensional Framework for Analyzing and Evaluating Agent Skills

arXiv:2610.01506v1 Announce Type: new Abstract: As agents evolve from single-tool systems into modular, composite architectures, skills are becoming an important mechanism for capability development a

2 Oct 2026

T2SPO: Trajectory-to-Step Policy Optimization for Agentic Reinforcement Learning

arXiv:2610.00388v1 Announce Type: cross Abstract: Reinforcement learning enables large language model (LLM) agents to learn multi-step behaviors through interaction with their environments. However, r

2 Oct 2026

After a Decade: Bringing Shadow Removal into the Real World with Agentic Training Data

arXiv:2609.38607v1 Announce Type: cross Abstract: Shadow removal looks nearly solved on established benchmarks, yet remains brittle in the real world. Models have advanced; the paired training data th

Agent Error Dataset: Scaling 50,000 Error--Diagnosis Pairs for Failure Analysis and Error-Aware Post-Training

arXiv:2609.40111v1 Announce Type: new Abstract: An unsuccessful LLM agent rollout contains more information than its final reward: the observations available to the agent, the actions it chose, and th

Cogentic: Multi-Agent Orchestration for Automated Proof Discovery

arXiv:2609.40324v1 Announce Type: new Abstract: We present Cogentic, a multi-agent harness for automated proof discovery on open research problems. While frontier language models can generate strong m

From DNA Design to DNA Slimming: Auditable Agentic Discovery of a Deletion-Only Designer

model-releasesarxiv-cs-lg

arXiv:2609.40143v1 Announce Type: new Abstract: Compact regulatory DNA can free up space in vector payloads, reduce synthesis and assay burden, and expose which sequence features drive predicted activ

JuryFlow: Disagreement-Guided Human-in-the-Loop Multi-Agent Evaluation

arXiv:2609.40103v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as automated judges for AI-generated content, yet a single judge is unreliable and even a panel o

agentsarxiv-cs-cl

Safety of Latent Communication in Multi-Agent Systems

arXiv:2609.39788v1 Announce Type: new Abstract: Latent communication enables multi-agent systems to exchange information directly in internal representation space, reducing the token, computation, and