Search: “tool-use”

DUET: Co-Evolving Solver and Grader Agents

arXiv:2610.04087v1 Announce Type: new Abstract: Agentic workflows are increasingly used across domains such as technology, finance, and enterprise operations. As these agents become more widely deploy

agentsarxiv-cs-lg

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

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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

safetyarxiv-cs-lg

6 Oct 2026

Monitorability Disposition in Large Reasoning Models

arXiv:2610.04914v1 Announce Type: cross Abstract: Monitoring the chain-of-thought (CoT) of large reasoning models (LRMs) is a common way to detect misbehavior in real-world practice. However, current

safetyarxiv-cs-lg

MultiLoc: Look Around As You Localize for Fast And Robust Visual Re-localization

model-releasesarxiv-cs-cv

arXiv:2603.27170v2 Announce Type: replace Abstract: Relative camera pose is a basic geometric cue for visual re-localization and scene understanding. When using images alone, visual evidence may not s

Recursive Self-Improvement of Visuomotor Policies through Local Recovery Supervision

arXiv:2610.05151v1 Announce Type: new Abstract: Visuomotor policies can execute familiar tasks yet lack the corrective behavior needed after their own mistakes. We present a framework for recursive se

safetyarxiv-cs-ro

A GHOST in Long-Horizon Agents: Governance Hazard from Overlooked Safety Constraints across Turns

arXiv:2610.02664v1 Announce Type: new Abstract: Long-horizon agents are now playing an increasingly significant role in assisting humans with complex problem-solving. However, it is exactly their exte

D2K-Bench: Can LLM Agents Turn Expert Designs into Efficient GPU Kernels?

arXiv:2610.03226v1 Announce Type: cross Abstract: GPU kernels generated by large language model (LLM) agents can remain less efficient than expert implementations, but runtime alone does not reveal ho

Dynamic LLM Routers are Often Misguided

arXiv:2610.02762v1 Announce Type: new Abstract: Dynamic LLM routers promise to cut inference costs by sending each query to the cheapest model that can answer it correctly. We analyze six commercial r

HyperBrowseComp: A Multilingual and Multimodal Stress Test for Web-Browsing Agents

arXiv:2610.03574v1 Announce Type: new Abstract: We introduce HyperBrowseComp, a multilingual and multimodal browsing benchmark comprising 423 manually authored and human-validated questions across 13

LEAP: Learning Efficient Action Proposals For LLM Agents

arXiv:2610.02670v1 Announce Type: cross Abstract: LLM agents are known to be slow in rollouts. An agent completes a task one step at a time. At each step, it reasons and then chooses an action to exec

Lost in the Request: How Communication Variation Disrupts Retrieval and Action in Email Agents

arXiv:2610.02627v1 Announce Type: new Abstract: An email assistant should not complete less work simply because a user phrases the same request differently. Yet most benchmarks test each task with onl

Prospective Hindsight: Self-Calibrating Reinforcement Learning via Prediction-Reality Gaps

arXiv:2610.02740v1 Announce Type: cross Abstract: Reinforcement learning for long-horizon agents relies on purely retrospective training signals: credit is assigned only after observing environmental

Reasoning Models Are Accurate but Unsound on Identification

arXiv:2610.03519v1 Announce Type: new Abstract: A reasoning model asked whether a causal effect is recoverable from observational data can fail in two ways: it refuses an identifiable query or answers

RoboBridge: A Self-Evolving Embodied Agent Framework for Sim-to-Real Transfer

arXiv:2610.02717v1 Announce Type: new Abstract: A key challenge in bringing embodied intelligence into the real world is transferring capabilities from simulation to reality and enabling agents to con

safetyarxiv-cs-ro

Securing Computer-Use Agents Against Branch Steering Attacks

arXiv:2610.03089v1 Announce Type: cross Abstract: Modern Computer Use Agents (CUAs) directly interact with graphical user interfaces and execute third-party web tools, exposing them to indirect prompt

Sentry: Learning to Recover from LLM Agent Failures at Test Time

arXiv:2610.02994v1 Announce Type: cross Abstract: LLM agents often fail mid-task due to invalid tool calls, repeated actions, or poorly grounded reasoning, and learning from these failures is a path 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

Local Ai

When Does Synthetic Relational Data Teach Models to Use Relations? Tracing Predictive Structure from Pretraining Data to Model Behavior

arXiv:2610.03057v1 Announce Type: new Abstract: Relational foundation models are increasingly pretrained on synthetic databases, yet downstream benchmarks reveal little about why one synthetic corpus

local-aiarxiv-cs-lg

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

CineMR: Tool-Integrated Vision-Language Reasoning for Quantitative Cardiac MRI Assessment

arXiv:2610.01166v1 Announce Type: cross Abstract: Cardiovascular magnetic resonance (CMR), including cine imaging, is a reference standard for the noninvasive assessment of cardiac morphology and vent

KaliBench: A Fine-Grained Benchmark for Cybersecurity Tool Use on Kali Linux with Runtime-Free Verifiable Rewards

arXiv:2610.02206v1 Announce Type: cross Abstract: LLMs are increasingly applied to cybersecurity workflows, where they are expected to translate analysts' intent into tool invocations. However, existi

Kepler: Auditable World Models for ARC-AGI-3

arXiv:2610.00834v1 Announce Type: new Abstract: ARC-AGI-3 evaluates agents in interactive environments whose rules and objectives must be inferred from observation. We present Kepler, an open-source h

Knowing When to Yield: Grounded Arbitration of User Corrections in Text-Based Embodied Agents

arXiv:2610.00282v1 Announce Type: new Abstract: How should an embodied agent respond when a person's correction may be wrong? We formulate grounded correction arbitration as a choice among accepting,

OmniSeek: Native Tool Integration for Multi-turn Audio-Visual Reasoning

arXiv:2610.02181v1 Announce Type: new Abstract: We present OmniSeek, an agentic framework that transforms an Omni Large Language Model (Omni-LLM) into an active, multi-turn reasoning agent with native

safetyarxiv-cs-cv

PhGPO: Pheromone-Guided Policy Optimization for Long-Horizon Tool Planning

arXiv:2602.13691v2 Announce Type: replace Abstract: Recent advancements in Large Language Model (LLM) agents have demonstrated strong capabilities in executing complex tasks through tool use. However,

Proof-Gated Signing: Solver-Checked Transaction Guards that Hold Under State Drift for Onchain AI Agents

arXiv:2610.00354v1 Announce Type: cross Abstract: AI agents that control wallets read attacker-reachable content, so they can be steered into proposing harmful transactions. The usual last line of def

Reducing Cognitive Overhead in Tool Use via Multi-Small-Agent Reinforcement Learning

arXiv:2508.08882v5 Announce Type: replace Abstract: Recent advances in multi-agent systems highlight the potential of specialized small agents that collaborate via division of labor. Existing tool-int

Revision-Aware Independent Agent Graphs for Dynamic Reasoning

arXiv:2610.01249v1 Announce Type: new Abstract: Conventional reasoning protocols present a fixed, preselected task, so they cannot test whether an agent propagates relevant updates, preserves unaffect

Scientific Agents: Evaluating Profession-Specific System Prompts on Scientific Tasks

arXiv:2610.00084v1 Announce Type: new Abstract: Detailed profession-specific system prompts raise token use and estimated cost per response without a consistent accuracy gain. We evaluate Scientific A

SkillSpec: Consensus-Gated Agent Skill Evolution via Representation Specialization

arXiv:2610.00704v1 Announce Type: new Abstract: Natural-language skills are textual procedural memories through which large language model (LLM) agents retain reusable task knowledge without updating

agentsarxiv-cs-lg

The Delegation Danger Band: Why Mid-Capability Sub-Agents Over-Trust Inherited Stale State

arXiv:2610.00041v1 Announce Type: cross Abstract: Agent frameworks increasingly delegate work by forking sub-agents; a common default makes the child inherit the parent's full working context. We meas

A look at two opposing perspectives on AI agent sandboxing: infosec says labs need better containment while AI alignment says sandboxes cannot contain agents (Matthew Green/A Few Thoughts on Cryptographic Engineering)

Matthew Green / A Few Thoughts on Cryptographic Engineering: A look at two opposing perspectives on AI agent sandboxing: infosec says labs need better containment while AI alignment says sandboxes can

safetytechmeme

EvoGuard: An Extensible Agentic RL-based Framework for Practical and Evolving AI-Generated Image Detection

arXiv:2603.17343v3 Announce Type: replace Abstract: The rapid proliferation of AI-Generated Images (AIGIs) poses severe misinformation risks, making AIGI detection critical yet challenging. Traditiona

safetyarxiv-cs-cv

From Verification Failures to Reusable Guidance for Coding Agents

arXiv:2609.39022v1 Announce Type: cross Abstract: Coding agents need to establish that a program satisfies a specification and that the specification captures the requested behavior. We study how expe

GraphForge: Training Working Agents with Graph-Anchored Workspace Synthesis

model-releasesarxiv-cs-cl

arXiv:2609.38923v1 Announce Type: new Abstract: Working agents need to read diverse files, coordinate tools, and produce deliverables. Training such agents requires tasks built on many real files with

GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives

arXiv:2609.39601v1 Announce Type: cross Abstract: Precise grounding matters. It specifies which object is the target and where that object is, even in clutter and for tiny objects, and it has to be fa

RealWorldShop: Benchmarking and Improving Conversational Shopping Agents in Real-World E-commerce

arXiv:2609.38974v1 Announce Type: new Abstract: Large language models are reshaping ecommerce from static recommenders into interactive shopping assistants, yet real-world shopping requires session-le

Rethinking Multi-Image Re-Representation in Multi-Image Understanding

arXiv:2609.39363v1 Announce Type: cross Abstract: Multi-image understanding requires MLLMs not only to recognise the content of individual images, but also to organise visual evidence distributed acro

The Backdrop Exposes What the World Around an Agent Costs It

arXiv:2609.38469v1 Announce Type: cross Abstract: Agent benchmarks test agents in worlds that stay still. Deployed agents work in worlds that other people also change. Someone texts the agent to send

Who Verifies the Graph? Misspecification Attacks on Causal Action Verification for Language Agents

arXiv:2609.40027v1 Announce Type: new Abstract: Causal action verifiers gate an agent's state-changing tool calls by checking whether each proposed intervention is identifiable against a committed act

WorldAuditBench: Interactive 3D World Auditing with Multimodal Agents

arXiv:2609.40325v1 Announce Type: new Abstract: As interactive 3D worlds are increasingly used to study intelligent behavior, it becomes important to develop efficient pipelines for identifying anomal

Can Language Models Learn to Forecast Stock Prices

model-releasesarxiv-cs-cl

arXiv:2609.36914v1 Announce Type: new Abstract: Post-training has been shown to significantly improve language models' performance on tasks with verifiable outcomes, including mathematical reasoning,

Evaluating Test-Time Scaling of General LLM Agents

arXiv:2602.18998v2 Announce Type: replace Abstract: LLM agents are increasingly expected to operate as general-purpose systems that resolve real-world user requests, yet their dynamic scaling behavior

MCPTox: A Benchmark for Tool Poisoning Attack on Real-World MCP Servers

model-releasesarxiv-cs-lg

arXiv:2508.14925v2 Announce Type: replace-cross Abstract: By providing a standardized interface for LLM agents to interact with external tools, the Model Context Protocol (MCP) is quickly becoming a c

Skill2Env: Capability-Oriented Environment Synthesis from Skills for General Agents

arXiv:2609.33772v2 Announce Type: replace Abstract: Executable environments are critical for post-training agents on tasks that require tool use and multi-step interaction, but constructing executable

AgentPerfBench: A Benchmarking and Evaluation Suite for Inference Performance of Agentic LLMs

model-releasesarxiv-cs-lg

arXiv:2609.34683v1 Announce Type: new Abstract: The optimization of LLM serving engines, such as vLLM and SGLang, is largely benchmark-driven: optimizations, scheduling policies, hardware and system d

29 Sept 2026

DexTaG: Tactile-as-Guidance in Reinforcement Learning for Dexterous Manipulation

arXiv:2609.33882v1 Announce Type: new Abstract: Glove-based motion capture is emerging as a scalable approach to collecting dexterous-hand demonstration data. However, due to the kinematic gap between

safetyarxiv-cs-ro

29 Sept 2026

EEGAgentBench: Benchmarking LLM Agents on Short- and Long-Horizon EEG Analysis