---
title: "Who cites ToolLLM: Facilitating Large Language Models to…"
description: "493 papers of the Elamur Research library cite «ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/qin-2023-toolllm-facilitating-large-language-models/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/qin-2023-toolllm-facilitating-large-language-models/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [ToolLLM: Facilitating Large Language Models to…](https://md.research.elamur.ai/free/en/papers/qin-2023-toolllm-facilitating-large-language-models/) / cited by

# Who cites «ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs»

493 papers of our library cite it (of the 140,884 whose bibliographies we read) · 30 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/qin-2023-toolllm-facilitating-large-language-models/)

1. [**A Survey on Evaluation of Large Language Models**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,640 citations*](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-large-language-models/)
2. [**A Survey of Large Language Models**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,847 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/)
3. [**A Comprehensive Overview of Large Language Models**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,286 citations*](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/)
4. [**C-Pack: Packed Resources For General Chinese Embeddings**Shitao Xiao, Zheng Liu, Peitian Zhang, et al.*2023 · 920 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2023-c-pack-packed-resources/)
5. [**Benchmarking Large Language Models in Retrieval-Augmented Generation**Jiawei Chen, Hongyu Lin, Xianpei Han, et al.*2023 · 624 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-benchmarking-large-language-models-retrieval/)
6. [**MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework**Sirui Hong, Mingchen Zhuge, Jiaqi Chen, et al.*2023 · 615 citations*](https://md.research.elamur.ai/free/en/papers/hong-2023-metagpt-meta-programming-multi/)
7. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code**Naman Jain, King Han, Alex Gu, et al.*2024 · 540 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
8. [**Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters**Charlie Snell, Jaehoon Lee, Kelvin Xu, et al.*2024 · 524 citations*](https://md.research.elamur.ai/free/en/papers/snell-2024-scaling-llm-test-time-compute/)
9. [**Query Rewriting in Retrieval-Augmented Large Language Models**Xinbei Ma, Yeyun Gong, Pengcheng He, et al.*2023 · 383 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-query-rewriting-retrieval-augmented-large/)
10. [**ChatDev: Communicative Agents for Software Development**Chen Qian, Wei Liu, Hongzhang Liu, et al.*2023 · 373 citations*](https://md.research.elamur.ai/free/en/papers/qian-2023-chatdev-communicative-agents-software/)
11. [**Kimi K2: Open Agentic Intelligence**Kimi Team, Yifan Bai, Yiping Bao, et al.*2025 · 331 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k2-open-agentic/)
12. [**InternLM2 Technical Report**Zheng Cai, Maosong Cao, Haojiong Chen, et al.*2024 · 299 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-internlm2-technical-report/)
13. [**API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs**Minghao Li, Yingxiu Zhao, Bowen Yu, et al.*2023 · 281 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-api-bank-comprehensive-benchmark-tool/)
14. [**On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey**Lin Long, Rui Wang, Ruixuan Xiao, et al.*2024 · 236 citations*](https://md.research.elamur.ai/free/en/papers/long-2024-llms-driven-synthetic-data-generation/)
15. [**TrustLLM: Trustworthiness in Large Language Models**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
16. [**AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors**Weize Chen, Yusheng Su, Jingwei Zuo, et al.*2023 · 210 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-agentverse-facilitating-multi-agent/)
17. [**OpenHands: An Open Platform for AI Software Developers as Generalist Agents**Xingyao Wang, Boxuan Li, Yufan Song, et al.*2024 · 190 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-openhands-open-platform-ai/)
18. [**RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models**Zekun Moore Wang, Zhongyuan Peng, Haoran Que, et al.*2023 · 186 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-rolellm-benchmarking-eliciting-enhancing-role/)
19. [**Evaluating Large Language Models: A Comprehensive Survey**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
20. [**ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases**Qiaoyu Tang, Ziliang Deng, Hongyu Lin, et al.*2023 · 172 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-toolalpaca-generalized-tool-learning-language/)
21. [**WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models**Hongliang He, Wenlin Yao, Kaixin Ma, et al.*2024 · 168 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-webvoyager-building-end-end-web/)
22. [**AgentTuning: Enabling Generalized Agent Abilities for LLMs**Aohan Zeng, Mingdao Liu, Rui Lu, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2023-agenttuning-enabling-generalized-agent/)
23. [**Executable Code Actions Elicit Better LLM Agents**Xingyao Wang, Yangyi Chen, Lifan Yuan, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-executable-code-actions-elicit-better/)
24. [**Agent Laboratory: Using LLM Agents as Research Assistants**Samuel Schmidgall, Yusheng Su, Ze Wang, et al.*2025 · 136 citations*](https://md.research.elamur.ai/free/en/papers/schmidgall-2025-agent-laboratory-using-llm/)
25. [**MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback**Xingyao Wang, Zihan Wang, Jiateng Liu, et al.*2023 · 136 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-mint-evaluating-llms-multi-turn/)
26. [**From Persona to Personalization: A Survey on Role-Playing Language Agents**Jiangjie Chen, Xintao Wang, Rui Xu, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/)
27. [**DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments**Yuxiang Zheng, Dayuan Fu, Xiangkun Hu, et al.*2025 · 108 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2025-deepresearcher-scaling-deep-research-reinforcement/)
28. [**LegalAgentBench: Evaluating LLM Agents in Legal Domain**Haitao Li, Junjie Chen, Jingli Yang, et al.*2025 · 60 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-legalagentbench-evaluating-llm-agents-legal/)
29. [**Designing LLM Agents for User-Centered Language Service Selection**Ryoichiro Ogawa, Donghui Lin, Fumito Uwano*2026*](https://md.research.elamur.ai/free/en/papers/ogawa-2026-designing-llm-agents-user-centered/)
30. [**Survey of Tool Use in Large Language Models (大语言模型的工具使用综述)**Yining Zheng (郑逸宁), Zhen Yu (余镇), Bufan Li (李不凡), et al.*2025*](https://md.research.elamur.ai/free/en/papers/zheng-2025-tool-use-large/)

463 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/qin-2023-toolllm-facilitating-large-language-models/) — ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs