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Tool learning, which enables large language models (LLMs) to utilize external tools effectively, has garnered increasing attention for its potential to revolutionize productivity across industries.
Did the Model Understand the Question?
Pramod Kaushik Mudrakarta, Ankur Taly, Mukund Sundararajan, and Kedar Dhamdhere · 2018
Earlier work this paper cites.
Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study
Jinlan Fu, Pengfei Liu, and Qi Zhang · 2020
Earlier work this paper cites.
Shortcut Learning in Deep Neural Networks
Robert Geirhos, Jörn-Henrik Jacobsen, Claudio Michaelis, Richard Zemel, Wieland Brendel, Matthias Bethge, and Felix A. Wichmann · 2020
Earlier work this paper cites.
Stable Learning Establishes some Common Ground between Causal Inference and Machine Learning
Peng Cui and Susan Athey · 2022
Earlier work this paper cites.
Identifying and mitigating spurious correlations for improving robustness in NLP models
Tianlu Wang, Rohit Sridhar, Diyi Yang, and Xuezhi Wang · 2022
Earlier work this paper cites.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, brian ichter, Fei Xia, Ed Chi, Quoc V Le, and Denny Zhou · 2022
Earlier work this paper cites.
Did the Models Understand Documents? Benchmarking Models for Language Understanding in Document-Level Relation Extraction
Haotian Chen, Bingsheng Chen, and Xiangdong Zhou · 2023
Earlier work this paper cites.
ToolTalk: Evaluating Tool-Usage in a Conversational Setting, November 2023
Nicholas Farn and Richard Shin · 2023
Earlier work this paper cites.
API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs
Minghao Li, Yingxiu Zhao, Bowen Yu, Feifan Song, Hangyu Li, Haiyang Yu, Zhoujun Li, Fei Huang, and Yongbin Li · 2023
Earlier work this paper cites.
GPT-4 Technical Report, March 2023
OpenAI · 2023
Earlier work this paper cites.
Tool learning with foundation models
Yujia Qin, Shengding Hu, Yankai Lin, Weize Chen, Ning Ding, Ganqu Cui, Zheni Zeng, Yufei Huang, Chaojun Xiao, Chi Han, et al · 2023
Earlier work this paper cites.
Toolformer: Language models can teach themselves to use tools
Timo Schick, Jane Dwivedi-Yu, Roberto Dessi, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom · 2023
Earlier work this paper cites.
RestGPT: Connecting large language models with real-world restful apis
Yifan Song, Weimin Xiong, Dawei Zhu, Wenhao Wu, Han Qian, Mingbo Song, Hailiang Huang, Cheng Li, Ke Wang, Rong Yao, et al · 2023
Earlier work this paper cites.
NexusRaven: Surpassing the state-of-the-art in open-source function calling LLMs, 2023
Nexusflow.ai team · 2023
Cited alongside, same era.
API-BLEND: A Comprehensive Corpora for Training and Benchmarking API LLMs
Kinjal Basu, Ibrahim Abdelaziz, Subhajit Chaudhury, Soham Dan, Maxwell Crouse, Asim Munawar, Vernon Austel, Sadhana Kumaravel, Vinod Muthusamy, Pavan Kapanipathi, and Luis Lastras · 2024
Cited alongside, same era.
OODREB: Benchmarking State-of-the-Art Methods for Out-Of-Distribution Generalization on Relation Extraction
Haotian Chen, Houjing Guo, Bingsheng Chen, and Xiangdong Zhou · 2024
Cited alongside, same era.
Rethinking the Development of Large Language Models from the Causal Perspective: A Legal Text Prediction Case Study
Haotian Chen, Lingwei Zhang, Yiran Liu, and Yang Yu · 2024
Cited alongside, same era.
Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs, December 2024
Xingyu Chen, Jiahao Xu, Tian Liang, Zhiwei He, Jianhui Pang, Dian Yu, Linfeng Song, Qiuzhi Liu, Mengfei Zhou, Zhuosheng Zhang, Rui Wang, Zhaopeng Tu, Haitao Mi, and Dong Yu · 2024
Gorilla: Large Language Model Connected with Massive APIs
Shishir G. Patil, Tianjun Zhang, Xin Wang, and Joseph E. Gonzalez · 2024
Later among the works it cites.
ToolLLM: Facilitating large language models to master 16000+ real-world APIs
Yujia Qin, Shihao Liang, Yining Ye, Kunlun Zhu, Lan Yan, Yaxi Lu, Yankai Lin, Xin Cong, Xiangru Tang, Bill Qian, Sihan Zhao, Lauren Hong, Runchu Tian, Ruobing Xie, Jie Zhou, Mark Gerstein, dahai li, Zhiyuan Liu, and Maosong Sun · 2024
Later among the works it cites.
Tool Learning with Large Language Models: A Survey, May 2024
Changle Qu, Sunhao Dai, Xiaochi Wei, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Jun Xu, and Ji-Rong Wen · 2024
Later among the works it cites.
Towards Completeness-Oriented Tool Retrieval for Large Language Models
Changle Qu, Sunhao Dai, Xiaochi Wei, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Jun Xu, and Ji-Rong Wen · 2024
Later among the works it cites.
TaskBench: Benchmarking Large Language Models for Task Automation, November 2024
Yongliang Shen, Kaitao Song, Xu Tan, Wenqi Zhang, Kan Ren, Siyu Yuan, Weiming Lu, Dongsheng Li, and Yueting Zhuang · 2024
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
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Cited alongside, same era.
T-Eval: Evaluating the Tool Utilization Capability of Large Language Models Step by Step, January 2024
Zehui Chen, Weihua Du, Wenwei Zhang, Kuikun Liu, Jiangning Liu, Miao Zheng, Jingming Zhuo, Songyang Zhang, Dahua Lin, Kai Chen, and Feng Zhao · 2024
Cited alongside, same era.
Detecting hallucinations in large language models using semantic entropy
Sebastian Farquhar, Jannik Kossen, Lorenz Kuhn, and Yarin Gal · 2024
Cited alongside, same era.
StableToolBench: Towards Stable Large-Scale Benchmarking on Tool Learning of Large Language Models
Zhicheng Guo, Sijie Cheng, Hao Wang, Shihao Liang, Yujia Qin, Peng Li, Zhiyuan Liu, Maosong Sun, and Yang Liu · 2024
Cited alongside, same era.
Large language models cannot self-correct reasoning yet
Jie Huang, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Wei Yu, Xinying Song, and Denny Zhou · 2024
Cited alongside, same era.
MetaTool benchmark for large language models: Deciding whether to use tools and which to use
Yue Huang, Jiawen Shi, Yuan Li, Chenrui Fan, Siyuan Wu, Qihui Zhang, Yixin Liu, Pan Zhou, Yao Wan, Neil Zhenqiang Gong, and Lichao Sun · 2024
Cited alongside, same era.
Tool-augmented reward modeling
Lei Li, Yekun Chai, Shuohuan Wang, Yu Sun, Hao Tian, Ningyu Zhang, and Hua Wu · 2024
Cited alongside, same era.
ToolACE: Winning the Points of LLM Function Calling, September 2024
Weiwen Liu, Xu Huang, Xingshan Zeng, Xinlong Hao, Shuai Yu, Dexun Li, Shuai Wang, Weinan Gan, Zhengying Liu, Yuanqing Yu, Zezhong Wang, Yuxian Wang, Wu Ning, Yutai Hou, Bin Wang, Chuhan Wu, Xinzhi Wang, Yong Liu, Yasheng Wang, Duyu Tang, Dandan Tu, Lifeng Shang, Xin Jiang, Ruiming Tang, Defu Lian, Qun Liu, and Enhong Chen · 2024
Cited alongside, same era.
Learning to Use Tools via Cooperative and Interactive Agents, June 2024
Zhengliang Shi, Shen Gao, Xiuyi Chen, Yue Feng, Lingyong Yan, Haibo Shi, Dawei Yin, Pengjie Ren, Suzan Verberne, and Zhaochun Ren · 2024
Later among the works it cites.
Voyager: An open-ended embodied agent with large language models
Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi Fan, and Anima Anandkumar · 2024
Later among the works it cites.
ToolSword: Unveiling Safety Issues of Large Language Models in Tool Learning Across Three Stages
Junjie Ye, Sixian Li, Guanyu Li, Caishuang Huang, Songyang Gao, Yilong Wu, Qi Zhang, Tao Gui, and Xuanjing Huang · 2024
Later among the works it cites.
CRAFT: Customizing LLMs by creating and retrieving from specialized toolsets
Lifan Yuan, Yangyi Chen, Xingyao Wang, Yi Fung, Hao Peng, and Heng Ji · 2024
Later among the works it cites.
InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents, August 2024
Qiusi Zhan, Zhixiang Liang, Zifan Ying, and Daniel Kang · 2024
Later among the works it cites.
Larger and more instructable language models become less reliable
Lexin Zhou, Wout Schellaert, Fernando Martínez-Plumed, Yael Moros-Daval, Cèsar Ferri, and José Hernández-Orallo · 2024
Later among the works it cites.
Qwen2.5 Technical Report, January 2025
Qwen, An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, Huan Lin, Jian Yang, Jianhong Tu, Jianwei Zhang, Jianxin Yang, Jiaxi Yang, Jingren Zhou, Junyang Lin, Kai Dang, Keming Lu, Keqin Bao, Kexin Yang, Le Yu, Mei Li, Mingfeng Xue, Pei Zhang, Qin Zhu, Rui Men, Runji Lin, Tianhao Li, Tianyi Tang, Tingyu Xia, Xingzhang Ren, Xuancheng Ren, Yang Fan, Yang Su, Yichang Zhang, Yu Wan, Yuqiong Liu, Zeyu Cui, Zhenru Zhang, and Zihan Qiu · 2025
Closest in time.
Seal-Tools: Self-instruct Tool Learning Dataset for Agent Tuning and Detailed Benchmark
Mengsong Wu, Tong Zhu, Han Han, Chuanyuan Tan, Xiang Zhang, and Wenliang Chen · 2025
Closest in time.