Tool-Using Agents

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31 papers in the last four weeks, up 210% on the four weeks before. 0.3% of all new papers.

Jul 13Week of Sep 28

Latest papers 199

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R2V Agent: Teaching SLMs When to Ask for Help
May 15, 2026Raghu Vamshi Hemadri, Humaira Firdowse Mohammed, Rishabh Maheshwary +5AI Agent Reliability Tool-Augmented Language Model Agents
New York University Tandon School of Engineering · University of California, San Diego · ServiceNow Research +3
ColPackAgent: Agent-Skill-Guided Hard-Particle Monte Carlo Workflows for Colloidal Packing
May 15, 2026Lijie Ding, Changwoo DoAgentic Workflows AI Agent Benchmarks
Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Multi-Agentic Approach for History Matching of Oil Reservoirs
May 14, 2026Linar Samigullin, Sergei Shumilin, Evgeny BurnaevMulti-Agent Orchestration LLM Agent Orchestration
Skoltech, AI Center, Moscow, Russia · AIRI, Moscow, Russia
ChromaFlow: A Negative Ablation Study of Orchestration Overhead in Tool-Augmented Agent Evaluation
May 13, 2026Tarun MittalAI Agent Reliability LLM Agent Orchestration
Octave-X
CRANE: Constrained Reasoning Injection for Code Agents via Nullspace Editing
May 13, 2026Mingzhi Zhu, Michele Merler, Raju Pavuluri +1Software Engineering Agents Agentic Code Generation
Rensselaer Polytechnic Institute Troy, NY 12180 · IBM Research Yorktown Heights, NY 10598
RS-Claw: Progressive Active Tool Exploration via Hierarchical Skill Trees for Remote Sensing Agents
May 13, 2026Liangtian Liu, Zeyuan Wang, Ziyu Li +8Remote Sensing Image Understanding Tool-Using Agents
School of Geosciences and Info-Physics, Central South University, Changsha 410083, China · School of Resources and Environment, University of Electronic Science and Technology of China, Xian 710071, China · School of Earth Sciences and Spatial Information Engineering, Hunan University of Science and Technology, Xiangtan 411201, China +1
Speculative Interaction Agents: Building Real-Time Agents with Asynchronous I/O and Speculative Tool Calling
May 13, 2026Coleman Hooper, Minwoo Kang, Suhong Moon +7Tool-Using Agents LLM Agents
University of California, Berkeley · ICSI · LBNL
No Action Without a NOD: A Heterogeneous Multi-Agent Architecture for Reliable Service Agents
May 12, 2026Zixu Yang, Hang Zheng, Nan Jiang +5AI Agent Reliability Multi-Agent LLM Systems
1X-LANCE Lab, School of Computer Science, Shanghai Jiao Tong University, Shanghai, China · 2Shanghai Innovation Institution, Shanghai, China · 3Jiangsu Key Lab of Language Computing, Suzhou, China
When Simulation Lies: A Sim-to-Real Benchmark and Domain-Randomized RL Recipe for Tool-Use Agents
May 12, 2026Xiaolin Zhou, Aojie Yuan, Zheng Luo +12Domain Randomization AI Agent Benchmarks
Arizona State University · University of Southern California · University of Pennsylvania +2
Can LLM Agents Respond to Disasters? Benchmarking Heterogeneous Geospatial Reasoning in Emergency Operations
May 12, 2026Junjue Wang, Weihao Xuan, Heli Qi +7LLM Agent Evaluation Geospatial Reasoning
1The University of Tokyo · 2RIKEN AIP · 3Waseda University +1
The Semantic Training Gap: Ontology-Grounded Tool Architectures for Industrial AI Agent Systems
May 11, 2026Grama ChethanLLM Grounding LLM Hallucination Mitigation
Siemens Digital Industries Software, Plano, TX, United States
ComplexMCP: Evaluation of LLM Agents in Dynamic, Interdependent, and Large-Scale Tool Sandbox
May 11, 2026Yuanyang Li, Xue Yang, Longyue Wang +2LLM Agent Evaluation AI Agent Benchmarks
1Zhejiang University · 2Zhejiang Lab · 3Alibaba Group
Agent-First Tool API: A Semantic Interface Paradigm for Enterprise AI Agent Systems
May 11, 2026Kai PanTool-Using Agents AI Agent Governance
A2A Lab
Security Risks in Tool-Enabled AI Agents: A Systematic Analysis of Privileged Execution Environments
May 10, 2026Hardik GoelAI Agent Security Tool-Using Agents
Microsoft Corporation, USA
CIVeX: Causal Intervention Verification for Language Agents
May 9, 2026Fabio RovaiStructural Causal Models Tool-Using Agents
The Tesseract Academy
Octopus Protocol: One-Shot Hardware Discovery and Control for AI Agents via Infrastructure-as-Prompts
May 9, 2026Quilee Simeon, Justin M. Wei, Yile FanRobotics AI Control
MIT · Harvard
AI-Care: A Conversational Agentic System for Task Coordination in Alzheimer's Disease Care
May 8, 2026Preyash Yadav, Michelle Cohn, Priyanka Koppolu +5Alzheimer's Disease Tool-Using Agents
Department of Computer Science University of California, Davis Davis, USA · Department of Linguistics University of California, Davis Davis, USA · Department of Neurology University of California, Davis Sacramento, USA +1
Do Agents Need to Plan Step-by-Step? Rethinking Planning Horizon in Data-Centric Tool Calling
May 8, 2026Naoki Otani, Nikita Bhutani, Hannah Kim +2Long-Horizon Planning Tool-Using Agents
Megagon Labs Mountain View, California, USA
AgentEscapeBench: Evaluating Out-of-Domain Tool-Grounded Reasoning in LLM Agents
May 8, 2026Zhengkang Guo, Yiyang Li, Lin Qiu +7LLM Agent Evaluation Long-Horizon Agent Evaluation
1Fudan University · 2Meituan Longcat Team
Beyond the Black Box: Interpretability of Agentic AI Tool Use
May 7, 2026Hariom Tatsat, Ariye ShaterAI Agent Reliability Mechanistic Interpretability
Quantitative Analytics, Barclays
MANTRA: Synthesizing SMT-Validated Compliance Benchmarks for Tool-Using LLM Agents
May 7, 2026Ashwani Anand, Ivi Chatzi, Ritam Raha +1Computer-Use Agent Benchmarks AI Agent Reliability
Max Planck Institute for Software Systems, Kaiserslautern, Germany
LongSeeker: Elastic Context Orchestration for Long-Horizon Search Agents
May 6, 2026Yijun Lu, Rui Ye, Yuwen Du +3Web Search Agents Tool-Using Agents
Shanghai Jiao Tong University
Terminus-4B: Can a Smaller Model Replace Frontier LLMs at Agentic Execution Tasks?
May 4, 2026Spandan Garg, Vikram Nitin, Yufan HuangAI Coding Agents Small Language Models
Microsoft USA
Beyond State Machines: Executing Network Procedures with Agentic Tool-Calling Sequences
May 4, 2026Purna Sai Garigipati, Onur Ayan, Kishor Chandra Joshi +1LLM Agent Orchestration Tool-Using Agents
Heisenberg Research Center, Huawei Technologies Duesseldorf GmbH, 80992 Munich, Germany · Eindhoven University of Technology, Eindhoven, The Netherlands
TADI: Tool-Augmented Drilling Intelligence via Agentic LLM Orchestration over Heterogeneous Wellsite Data
Apr 30, 2026Rong LuLLM Agent Orchestration Tool-Using Agents
Reinforced Agent: Inference-Time Feedback for Tool-Calling Agents
Apr 29, 2026Anh Ta, Junjie Zhu, Shahin ShayandehMulti-Agent LLM Systems Tool-Use Evaluation
Apple
Bidirectional Semantic Complementary Tool Retrieval for Remote Sensing Agents
Apr 29, 2026Zeyuan Wang, Dongyang Hou, Cheng Yang +10Remote Sensing Tool-Using Agents
School of Geosciences and Info-Physics, Central South University, Changsha 410083, China. · School of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China. · Hunan Key Laboratory of Land Resources Evaluation and Utilization, Hunan Provincial Institute of Land and Resources Planning, Changsha 410013, China.
When Agents Look the Same: Quantifying Distillation-Induced Similarity in Tool-Use Behaviors
Apr 23, 2026Chenghao Yang, Yuning Zhang, Zhoufutu Wen +4Tool-Augmented Language Model Agents LLM Agent Evaluation
School of Cyber Science and Technology, USTC · Anhui Province Key Laboratory of Digital Security · 3M-A-P +1
ClawEnvKit: Automatic Environment Generation for Claw-Like Agents
Apr 20, 2026Xirui Li, Ming Li, Ion Stoica +2Agent Evaluation AI Agent Benchmarks
University of Maryland · 5Mohamed bin Zayed University of Artificial Intelligence · 2Arena +2
Architectural Design Decisions in AI Agent Harnesses
Apr 20, 2026Hu WeiLLM Agent Orchestration Tool-Using Agents

May 15, 2026, cs.LGJ/K move · Enter open · S save

R2V Agent: Teaching SLMs When to Ask for Help

Raghu Vamshi Hemadri, Humaira Firdowse Mohammed, Rishabh Maheshwary, Srivatsava Daruru+4

New York University Tandon School of Engineering · University of California, San Diego · ServiceNow Research+3

AI Agent Reliability Tool-Augmented Language Model Agents LLM Agent Workflow Optimization Tool-Using Agents LLM Agent Reliability LLM Agent Routing

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Efficient agentic systems should incur expensive frontier-model costs only on decisions where a cheaper local model is likely to fail. Existing LLM cascades usually route whole queries before execution, but task difficulty shifts mid-trajectory - after flaky tool calls, truncated observations, or compounding local errors - making pre-execution routing brittle. We introduce \textbf{R2V-Agent}, a risk-calibrated SLM-LLM routing framework for interactive agents. R2V combines four components: a distilled small language model (SLM) policy, a stronger teacher LLM, a lightweight process verifier that scores candidate actions at each step, and a calibrated step-level router. The router is our central contribution: after the SLM is trained, it estimates residual failure risk at each step and escalates only when teacher intervention is warranted. To make the routing problem well-defined, we first train a stable local SLM using a standard offline pipeline: behavioral cloning (BC) on teacher trajectories, followed by verifier-guided Direct Preference Optimization (DPO) with consistency regularization. The router is then trained on this fixed policy's residual failures using Brier-calibrated probability estimation and a Conditional Value-at-Risk (CVaR)-constrained objective that penalizes worst-case failures across perturbation seeds. Across HumanEval+, TextWorld, and TerminalBench with four SLM backbones, R2V improves the reliability-cost frontier: it achieves

94.3\%

HumanEval+ success with

0.60\%

LLM escalation, recovers TextWorld from

64.6\%

SLM-only success to

98.2\%

41.7\%

escalation, and reaches

93.3\%

TerminalBench success at

33.9\%

LLM calls, roughly half the heuristic-router cost.

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Latest papers 199