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Recently, tool-augmented LLMs have gained increasing attention.
The rating of chessplayers: Past and present
Arpad E Elo and Sam Sloan. 1978 · 1978
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
Earlier work this paper cites.
Openai: Introducing chatgpt
OpenAI. 2022 · 2022
Earlier work this paper cites.
Talm: Tool augmented language models
Aaron Parisi, Yao Zhao, and Noah Fiedel. 2022 · 2022
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Self-instruct: Aligning language model with self generated instructions
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A Smith, Daniel Khashabi, and Hannaneh Hajishirzi. 2022 · 2022
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React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2022 · 2022
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Extending context window of large language models via positional interpolation
Shouyuan Chen, Sherman Wong, Liangjian Chen, and Yuandong Tian. 2023 · 2023
Earlier work this paper cites.
Yilun Kong, Jingqing Ruan, Yihong Chen, Bin Zhang, Tianpeng Bao, Shiwei Shi, Guoqing Du, Xiaoru Hu, Hangyu Mao, Ziyue Li, et al. 2023 · 2023
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Api-bank: A benchmark for tool-augmented llms
Minghao Li, Feifan Song, Bowen Yu, Haiyang Yu, Zhoujun Li, Fei Huang, and Yongbin Li. 2023 · 2023
Earlier work this paper cites.
Taskmatrix. ai: Completing tasks by connecting foundation models with millions of apis
Yaobo Liang, Chenfei Wu, Ting Song, Wenshan Wu, Yan Xia, Yu Liu, Yang Ou, Shuai Lu, Lei Ji, Shaoguang Mao, et al. 2023 · 2023
Cited alongside, same era.
OpenAI. 2023 · 2023
Cited alongside, same era.
Gorilla: Large language model connected with massive apis
Shishir G Patil, Tianjun Zhang, Xin Wang, and Joseph E Gonzalez. 2023 · 2023
Cited alongside, same era.
Making language models better tool learners with execution feedback
Shuofei Qiao, Honghao Gui, Huajun Chen, and Ningyu Zhang. 2023 · 2023
Cited alongside, same era.
Toolllm: Facilitating large language models to master 16000+ real-world apis
On the tool manipulation capability of open-source large language models
Qiantong Xu, Fenglu Hong, Bo Li, Changran Hu, Zhengyu Chen, and Jian Zhang. 2023 · 2023
Later among the works it cites.
Gpt4tools: Teaching large language model to use tools via self-instruction
Rui Yang, Lin Song, Yanwei Li, Sijie Zhao, Yixiao Ge, Xiu Li, and Ying Shan. 2023 · 2023
Later among the works it cites.
Large language model as autonomous decision maker
Yining Ye, Xin Cong, Yujia Qin, Yankai Lin, Zhiyuan Liu, and Maosong Sun. 2023 · 2023
Later among the works it cites.
Rrhf: Rank responses to align language models with human feedback
Hongyi Yuan, Zheng Yuan, Chuanqi Tan, Wei Wang, Songfang Huang, and Fei Huang. 2023 · 2023
Later among the works it cites.
Anytool: Self-reflective, hierarchical agents for large-scale api calls
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Yujia Qin, Shihao Liang, Yining Ye, Kunlun Zhu, Lan Yan, Yaxi Lu, Yankai Lin, Xin Cong, Xiangru Tang, Bill Qian, et al. 2023 · 2023
Cited alongside, same era.
Tptu: Task planning and tool usage of large language model-based ai agents
Jingqing Ruan, Yihong Chen, Bin Zhang, Zhiwei Xu, Tianpeng Bao, Guoqing Du, Shiwei Shi, Hangyu Mao, Xingyu Zeng, and Rui Zhao. 2023 · 2023
Cited alongside, same era.
Toolalpaca: Generalized tool learning for language models with 3000 simulated cases
Qiaoyu Tang, Ziliang Deng, Hongyu Lin, Xianpei Han, Qiao Liang, and Le Sun. 2023 · 2023
Cited alongside, same era.
Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al. 2023 · 2023
Cited alongside, same era.
Visual chatgpt: Talking, drawing and editing with visual foundation models
Chenfei Wu, Shengming Yin, Weizhen Qi, Xiaodong Wang, Zecheng Tang, and Nan Duan. 2023 · 2023
Cited alongside, same era.
Rltf: Reinforcement learning from unit test feedback
Jiate Liu, Yiqin Zhu, Kaiwen Xiao, Qiang Fu, Xiao Han, Wei Yang, and Deheng Ye. 2023a
Cited in the paper.
Agentbench: Evaluating llms as agents
Xiao Liu, Hao Yu, Hanchen Zhang, Yifan Xu, Xuanyu Lei, Hanyu Lai, Yu Gu, Hangliang Ding, Kaiwen Men, Kejuan Yang, et al. 2023b
Cited in the paper.
Pangu-coder2: Boosting large language models for code with ranking feedback
Bo Shen, Jiaxin Zhang, Taihong Chen, Daoguang Zan, Bing Geng, An Fu, Muhan Zeng, Ailun Yu, Jichuan Ji, Jingyang Zhao, et al. 2023a
Cited in the paper.
Yu Du, Fangyun Wei, and Hongyang Zhang. 2024 · 2024
Closest in time.
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 · 2024
Closest in time.
From summary to action: Enhancing large language models for complex tasks with open world apis
Yulong Liu, Yunlong Yuan, Chunwei Wang, Jianhua Han, Yongqiang Ma, Li Zhang, Nanning Zheng, and Hang Xu. 2024 · 2024
Closest in time.
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. 2024 · 2024
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