Cover Image

GTA: A Benchmark for General Tool Agents

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Jize, Ma, Zerun, Li, Yining, Zhang, Songyang, Chen, Cailian, Chen, Kai, Le, Xinyi
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

GTA-2: Benchmarking General Tool Agents from Atomic Tool-Use to Open-Ended Workflows
by: Wang, Jize, et al.
Published: (2026)

DataChef: Cooking Up Optimal Data Recipes for LLM Adaptation via Reinforcement Learning
by: Chen, Yicheng, et al.
Published: (2026)

MIG: Automatic Data Selection for Instruction Tuning by Maximizing Information Gain in Semantic Space
by: Chen, Yicheng, et al.
Published: (2025)

GTA: Generating Long-Horizon Tasks for Web Agents at Scale
by: Huang, Tenghao, et al.
Published: (2026)

TREX: Automating LLM Fine-tuning via Agent-Driven Tree-based Exploration
by: Ma, Zerun, et al.
Published: (2026)

SAIL: Sample-Centric In-Context Learning for Document Information Extraction
by: Zhang, Jinyu, et al.
Published: (2024)

GTA: Grouped-head latenT Attention
by: Sun, Luoyang, et al.
Published: (2025)

FamilyTool: A Multi-hop Personalized Tool Use Benchmark
by: Wang, Yuxin, et al.
Published: (2025)

RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-Agents
by: Wang, Jize, et al.
Published: (2026)

Dissecting Tool-Integrated Reasoning: An Empirical Study and Analysis
by: Zhao, Yufeng, et al.
Published: (2025)

Rectifying LLM Thought from Lens of Optimization
by: Liu, Junnan, et al.
Published: (2025)

Coding Triangle: How Does Large Language Model Understand Code?
by: Zhang, Taolin, et al.
Published: (2025)

Ada-LEval: Evaluating long-context LLMs with length-adaptable benchmarks
by: Wang, Chonghua, et al.
Published: (2024)

RoTBench: A Multi-Level Benchmark for Evaluating the Robustness of Large Language Models in Tool Learning
by: Ye, Junjie, et al.
Published: (2024)

CompassJudger-2: Towards Generalist Judge Model via Verifiable Rewards
by: Zhang, Taolin, et al.
Published: (2025)

Are Your LLMs Capable of Stable Reasoning?
by: Liu, Junnan, et al.
Published: (2024)

PatRe: A Full-Stage Office Action and Rebuttal Generation Benchmark for Patent Examination
by: Wang, Qiyao, et al.
Published: (2026)

SciToolAgent: A Knowledge Graph-Driven Scientific Agent for Multi-Tool Integration
by: Ding, Keyan, et al.
Published: (2025)

ToolSword: Unveiling Safety Issues of Large Language Models in Tool Learning Across Three Stages
by: Ye, Junjie, et al.
Published: (2024)

TestAgent: Automatic Benchmarking and Exploratory Interaction for Evaluating LLMs in Vertical Domains
by: Wang, Wanying, et al.
Published: (2024)

Small LLMs Are Weak Tool Learners: A Multi-LLM Agent
by: Shen, Weizhou, et al.
Published: (2024)

FinMCP-Bench: Benchmarking LLM Agents for Real-World Financial Tool Use under the Model Context Protocol
by: Zhu, Jie, et al.
Published: (2026)

Deciphering Trajectory-Aided LLM Reasoning: An Optimization Perspective
by: Liu, Junnan, et al.
Published: (2025)

CompassJudger-1: All-in-one Judge Model Helps Model Evaluation and Evolution
by: Cao, Maosong, et al.
Published: (2024)

CompassVerifier: A Unified and Robust Verifier for LLMs Evaluation and Outcome Reward
by: Liu, Shudong, et al.
Published: (2025)

GAP: Graph-Based Agent Planning with Parallel Tool Use and Reinforcement Learning
by: Wu, Jiaqi, et al.
Published: (2025)

LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools?
by: Mo, Guozhao, et al.
Published: (2025)

Input Conditioned Graph Generation for Language Agents
by: Vierling, Lukas, et al.
Published: (2024)

Condor: Enhance LLM Alignment with Knowledge-Driven Data Synthesis and Refinement
by: Cao, Maosong, et al.
Published: (2025)

The Tool Decathlon: Benchmarking Language Agents for Diverse, Realistic, and Long-Horizon Task Execution
by: Li, Junlong, et al.
Published: (2025)

ALOHA: Empowering Multilingual Agent for University Orientation with Hierarchical Retrieval
by: Tao, Mingxu, et al.
Published: (2025)

TUMIX: Multi-Agent Test-Time Scaling with Tool-Use Mixture
by: Chen, Yongchao, et al.
Published: (2025)

ToolBeHonest: A Multi-level Hallucination Diagnostic Benchmark for Tool-Augmented Large Language Models
by: Zhang, Yuxiang, et al.
Published: (2024)

Benchmarking Data Science Agents
by: Zhang, Yuge, et al.
Published: (2024)

D-GARA: A Dynamic Benchmarking Framework for GUI Agent Robustness in Real-World Anomalies
by: Chen, Sen, et al.
Published: (2025)

ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios
by: Ye, Junjie, et al.
Published: (2024)

ToolGate: Contract-Grounded and Verified Tool Execution for LLMs
by: Liu, Yanming, et al.
Published: (2026)

SciAgent: Tool-augmented Language Models for Scientific Reasoning
by: Ma, Yubo, et al.
Published: (2024)

PruneTIR: Inference-Time Tool Call Pruning for Effective yet Efficient Tool-Integrated Reasoning
by: Zhang, Luan, et al.
Published: (2026)

InfoMosaic-Bench: Evaluating Multi-Source Information Seeking in Tool-Augmented Agents
by: Du, Yaxin, et al.
Published: (2025)