Tool-Using Language Agents

Follow this topic Ask about this topic

Tool-using language agents decide when and how to call external tools—such as APIs, databases, code interpreters, and personal applications—to gather information and act on a user's behalf. Common approaches include planning and workflow execution, retrieving and ranking relevant tools or skills, using memory from prior trajectories, and improving behavior through supervised fine-tuning or reinforcement learning. Benchmarks test agents in interactive settings such as web and API tasks, enterprise workflows, smart homes, and scientific research, measuring task completion alongside tool selection, efficiency, and safety. Agents still struggle with long tool chains, ambiguous references, partial information, and tool failures, creating a tension between autonomous execution and reliable, efficient, well-guarded behavior.

Latest papers

59 papers6 papers in the last four weeks, down 40% on the four weeks before. 0.0% of all new papers.

SPECMEM: Accelerating Agentic Tool Calling via Live Memory Management
Oct 22, 2026Zihe Song, Wenting Zhao, Ye Liu +4Tool-Using Language Agents LLM Inference Efficiency
Department of Computer Science, University of Illinois Chicago · Salesforce Research
Before Retrieval Begins: Safety and Tool-Use Decisions in LLM Agents
Oct 16, 2026Aditya Nawal, Manit Baser, Mohan GurusamyLLM Agent Safety Tool-Using Language Agents
National University of Singapore
TRACER: Trajectory-Aware Tool Retrieval for LLM Agents
Oct 15, 2026Tanish Kher, Sarvesh DK, Abedelkadir Asi +2Tool Selection for Language Model Agents LLM Tool Use
Microsoft
J-tau: A Fully Localized Japanese Benchmark for Tool-Agent-User Interaction
Oct 14, 2026Chihiro Yano, Jun Hirako, Hiroaki Yamagiwa +1AI Agent Benchmarks LLM Agent Evaluation
SB Intuitions Corp. · Nagoya University
AgentHop: A Diagnostic Benchmark for Agentic Multi-Hop Scientific Question Answering
Sep 28, 2026Chanhee Park, Jeongho Yoon, Sungbin Han +2Multi-Hop QA Tool-Augmented Language Model Agents
Korea University · Sookmyung Women’s University
SALMONN-duo: Adaptive Dual-System Coordination for Full-Duplex Voice Agents
Sep 28, 2026Wenyi Yu, Siyin Wang, Terumi Chiba +5LLM Agent Orchestration Tool-Using Language Agents
Tsinghua University · ByteDance
Learning from Failures: Heterogeneous Graph Memory for Small Language Model Tool-Using Agents
Sep 23, 2026Jiaxing Li, Lei Song, Rui Dong +1Graph-Based Agent Memory Long-Horizon LLM Agents
School of Computer Science and Engineering, Southeast University, Nanjing, China
Extending FunctionGemma for Practical On-Device Mobile Function Calling
Sep 21, 2026Ali Rezagholizadeh, Soheila SamieeOn-Device Language Model Inference Tool-Using Language Agents
UGrowAI
An Iterative LangGraph Agent for Text-to-SQL: Natural Language Access to the Chicago Crime Database
Sep 19, 2026Vigneshwar Ravi Rao, Rupesh Swarnakar, Fayeq Jeelani Syed†Text-to-SQL Tool-Using Language Agents
Luddy School of Informatics, Computing and Engineering, Indiana University, Indianapolis, Indiana, USA
RideWay: Benchmarking Efficient Task Completion for Tool-Using Language Agents
Sep 16, 2026Qingnuan Han, Boli Fang, Mingzhi Hou +1Tool-Use Evaluation AI Agent Benchmarks
Didi Global
Salesforce Koa: An Enterprise Language Model for Agentic Tool Use
Sep 14, 2026Zixiang Chen, Sufeng Niu, Yingchi Liu +23Tool-Augmented Language Model Agents Language Modeling
Salesforce Agentforce & AI Research
Fabrication After Tool Failure: Tool-Augmented Agents Assert Values Their Tools Did Not Return
Sep 13, 2026Arham Sethi, Arsen Kenzhebayev, Saanvi Paturi +3Tool-Augmented Language Model Agents Deception in Language Models
The Shishukunj International School · Haileybury Astana · UWCSEA East Campus +2
Realtime-Venus: A full-duplex interaction system with asynchronous delegation
Sep 12, 2026Ant GroupAudio-Visual Understanding Tool-Using Language Agents
Venus Team, Ant Group · Tsinghua University
The Menu Is an Execution Prior: State-Path Tool Menus for Online Agents
Sep 8, 2026Bo Yan, Weikai Lin, Song WangTool-Using Agents LLM Tool Use
Department of Computer Science & Institute of Artificial Intelligence, University of Central Florida · Department of Computer Science, University of Rochester
Toollery: Scaling LLM Agents to Thousands of Skills and Tools
Sep 2, 2026Xiangxi Tian, Ran GuanTool Selection for Language Model Agents LLM Agent Skill Retrieval
Laboratories, Huawei
Harness Engineering in LLM Tool Use via Agent-Native Reusable Tool Primitives
Sep 1, 2026Haibo Jin, Suijin Wang, Xucheng Yu +2Tool-Augmented Language Model Agents LLM Agent Orchestration
School of Information Sciences University of Illinois at Urbana-Champaign Champaign, IL 61820 · Independent Researcher Starc Institute
You Know What I Mean: A Benchmark for Agentic Conversational Reference Grounding
Aug 30, 2026Karen Fuchs, Uri Katz, Yoav GoldbergSoftware Engineering Agents Agentic Retrieval
Bar-Ilan University · Allen Institute for AI
Beyond Single-Turn Confidence: Trajectory-Adapted Uncertainty Quantification for LLM Agents
Aug 12, 2026Dylan Bouchard, Mohit Singh ChauhanConfidence Estimation in Language Models LLM Agent Evaluation
Diagnosing Tool-Selection Reasoning in LLM Agents with Canary Tools
Aug 5, 2026Atul Anand, Sourav ChattarajLLM Agent Evaluation Tool-Using Language Agents
UrbanAgent: A Tool-Augmented Agent for Cross-System Urban Tasks
Aug 4, 2026Jiayu Cao, Xingyuan Zeng, feiyu Li +6LLM Agent Evaluation AI Agent Benchmarks
TraceCompiler: Skill-Guided Mining and Compilation of LLM Agent Traces into Mostly Deterministic Workflows
Aug 3, 2026Salma El Yadouni, Guanyi LiAgentic Workflows LLM-Based Program Synthesis
EPFL · EPFL, Lausanne, Switzerland · Binome Technologies +1
Scores Are Not Decisions: Cost-Aware Stopping for Tool Acquisition in LLM Agents
Jul 29, 2026Yicheng Feng, Yan Zhang, Yan Cheng +1Decision-Focused Learning Tool-Using Agents
School of Advanced Manufacturing and Robotics, Peking University · Desautels Faculty of Management, McGill University · Business School, Shanghai University of Finance and Economics +1
Tools Are Not Islands: Set-Level Tool Retrieval for LLM Agents via Query-Conditioned Hyperedge Prediction
Jul 28, 2026Xinyi Hong, Pinjun Dong, Xinyang Yu +1Tool-Augmented Language Model Agents LLM Tool Use
School of Mathematical Sciences, Shanghai Jiao Tong University · Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University
GuardianAgentBench: Where Agents Fail and How to Guard Them
Jul 23, 2026Vishal Ishwar Naik, Chenyu Xu, Donna Dong +5AI Agent Reliability LLM Guardrails
Vectara, Inc., Palo Alto, CA, USA · Iowa State University, Ames, IA, USA
MagicSelector: Joint Optimization for Agent Tool Selection via Counterfactual Decomposition and Progressive Reranking
Jul 20, 2026HONOR Agentic Search Team, Zhengzong Chen, Lei Tang +27Learning to Rank LLM Planning
HONOR Agentic Search Team
Scalable LLM Agent Tool Access in the Cloud
Jul 17, 2026Mingxin Li, Enge Song, Yueshang Zuo +27LLM Tool Use Model Context Protocol
Nanjing University · Alibaba Cloud · Fudan University +3
A Formal Hierarchical Architecture for Agentic Orchestration with Stack-Based Execution and Lazy Discovery
Jul 13, 2026Prashant Devadiga, Abhishek, Adithya Mishra +9LLM Agent Orchestration Tool-Using Language Agents
UPI Help
Cross-Layer Misalignment Detection in Agent Skills: A Progressive Loading-Aware Contrastive Learning Approach
Jul 12, 2026Chengjun Zhang, Yang Gao, Jianna Hur +2Contrastive Learning Tool-Using Language Agents
Indiana University Bloomington Bloomington, Indiana, USA
DynamicMCPBench: A Trace-Grounded, Effect-Scored Benchmark for LLM Agents over Live MCP Servers
Jul 10, 2026Jerzy Kamiński, Ilya Galyukshev, Artem Kuznetsov +4Computer-Use Agent Benchmarks LLM Agent Evaluation
ITMO University · Central University
Beyond the Leaderboard: A Synthesis of Tool-Use, Planning, and Reasoning Failures in Large Language Model Agents
Jul 7, 2026Wael Albayaydh, Rui Zhao, Ivan FlechaisAI Agent Reliability LLM Agent Evaluation
University of Oxford

Oct 22, 2026J/K move · Enter open · S save

SPECMEM: Accelerating Agentic Tool Calling via Live Memory Management

Zihe Song, Wenting Zhao, Ye Liu, Yuanjie Zhu+3

Department of Computer Science, University of Illinois Chicago · Salesforce Research

Tool-Using Language Agents LLM Inference Efficiency Memory Management for LLM Agents Speculative Decoding

Open paper AskPDF arXiv

Tool-calling agents are mostly optimized for accuracy; in deployment, however, their growing cost is latency: every tool call is decoded autoregressively. Speculative decoding accelerates this without changing the output, and retrieved past calls make strong drafts under real use, where each user's behavior tends to repeat. Yet existing systems keep no cross-session memory, or build the draft store once and never update it. We propose SpecMem, a tool-call memory kept alive and managed throughout deployment: verified calls are written back online into bounded per-user stores with LRU eviction, and a side-effect gate defers irreversible calls until verification confirms. On multi-session, multi-user query streams served by three open-weight models, a frozen store steadily loses acceptance while SpecMem holds it: a 27% gap in mean accepted tokens (+11% to +34% across benchmarks, tracking how much novel work arrives after the store is built) and up to 1.74x wall-clock speedup. Ablations attribute the gain almost entirely to keeping the store live; local per-user scoping adds no acceptance but closes a measured cross-user leakage channel, and gating on declared side effects, rather than on retrieval confidence, is what eliminates irreversible mistakes.