NesTools: A Dataset for Evaluating Nested Tool Learning Abilities of Large Language Models

Gpt-4 technical report

Original

Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023

Earlier work this paper cites.

Qwen technical report

Original

Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, et al. 2023 · 2023

Earlier work this paper cites.

Metatool benchmark for large language models: Deciding whether to use tools and which to use

Original

Yue Huang, Jiawen Shi, Yuan Li, Chenrui Fan, Siyuan Wu, Qihui Zhang, Yixin Liu, Pan Zhou, Yao Wan, Neil Zhenqiang Gong, et al. 2023 · 2023

Earlier work this paper cites.

MultiTool-CoT: GPT-3 can use multiple external tools with chain of thought prompting

Tatsuro Inaba, Hirokazu Kiyomaru, Fei Cheng, and Sadao Kurohashi. 2023 · 2023

Earlier work this paper cites.

Mistral 7b

Original

Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 2023 · 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 · 2023

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Art: Automatic multi-step reasoning and tool-use for large language models

Original

Bhargavi Paranjape, Scott Lundberg, Sameer Singh, Hannaneh Hajishirzi, Luke Zettlemoyer, and Marco Tulio Ribeiro. 2023 · 2023

Earlier work this paper cites.

Gorilla: Large language model connected with massive apis

Original

Shishir G Patil, Tianjun Zhang, Xin Wang, and Joseph E Gonzalez. 2023 · 2023

Earlier work this paper cites.

Toolformer: Language models can teach themselves to use tools

Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom. 2023 · 2023

Earlier work this paper cites.

Taskbench: Benchmarking large language models for task automation

Original

Yongliang Shen, Kaitao Song, Xu Tan, Wenqi Zhang, Kan Ren, Siyu Yuan, Weiming Lu, Dongsheng Li, and Yueting Zhuang. 2023 · 2023

Cited alongside, same era.

Restgpt: Connecting large language models with real-world restful apis

Original

Yifan Song, Weimin Xiong, Dawei Zhu, Wenhao Wu, Han Qian, Mingbo Song, Hailiang Huang, Cheng Li, Ke Wang, Rong Yao, et al. 2023 · 2023

Cited alongside, same era.

Toolalpaca: Generalized tool learning for language models with 3000 simulated cases

Original

Qiaoyu Tang, Ziliang Deng, Hongyu Lin, Xianpei Han, Qiao Liang, Boxi Cao, and Le Sun. 2023 · 2023

Cited alongside, same era.

Self-instruct: Aligning language models with self-generated instructions

Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, and Hannaneh Hajishirzi. 2023 · 2023

Cited alongside, same era.

Planning, creation, usage: Benchmarking LLMs for comprehensive tool utilization in real-world complex scenarios

Shijue Huang, Wanjun Zhong, Jianqiao Lu, Qi Zhu, Jiahui Gao, Weiwen Liu, Yutai Hou, Xingshan Zeng, Yasheng Wang, Lifeng Shang, Xin Jiang, Ruifeng Xu, and Qun Liu. 2024 · 2024

Closest in time.

Mixtral of experts

Original

Albert Q Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, et al. 2024 · 2024

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Tool learning with large language models: A survey

Original

Changle Qu, Sunhao Dai, Xiaochi Wei, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Jun Xu, and Ji-Rong Wen. 2024 · 2024

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Seal-tools: Self-instruct tool learning dataset for agent tuning and detailed benchmark

Original

Mengsong Wu, Tong Zhu, Han Han, Chuanyuan Tan, Xiang Zhang, and Wenliang Chen. 2024 · 2024

Closest in time.