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The evolution of large language models (LLMs) has enhanced the planning capabilities of language agents in diverse real-world scenarios.
What Computers Still Can’t Do: A Critique of Artificial Reason
Hubert L. Dreyfus. 1992 · 1992
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Discourse on Method (Third Edition)
R. Descartes and D.A. Cress. 1998 · 1998
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Learning to ask good questions: Ranking clarification questions using neural expected value of perfect information
Sudha Rao and Hal Daumé III. 2018 · 2018
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Asking clarification questions in knowledge-based question answering
Jingjing Xu, Yuechen Wang, Duyu Tang, Nan Duan, Pengcheng Yang, Qi Zeng, Ming Zhou, and Xu Sun. 2019 · 2019
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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
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Generating clarifying questions for information retrieval
Hamed Zamani, Susan T. Dumais, Nick Craswell, Paul N. Bennett, and Gord Lueck. 2020 · 2020
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Building and evaluating open-domain dialogue corpora with clarifying questions
Mohammad Aliannejadi, Julia Kiseleva, Aleksandr Chuklin, Jeff Dalton, and Mikhail Burtsev. 2021 · 2021
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PACIFIC: Towards proactive conversational question answering over tabular and textual data in finance
Yang Deng, Wenqiang Lei, Wenxuan Zhang, Wai Lam, and Tat-Seng Chua. 2022 · 2022
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Lora: Low-rank adaptation of large language models
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022 · 2022
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Clam: Selective clarification for ambiguous questions with generative language models
Lorenz Kuhn, Yarin Gal, and Sebastian Farquhar. 2022 · 2022
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Paulius Micikevicius, Dusan Stosic, Neil Burgess, Marius Cornea, Pradeep Dubey, Richard Grisenthwaite, Sangwon Ha, Alexander Heinecke, Patrick Judd, John Kamalu, et al. 2022 · 2022
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Webshop: Towards scalable real-world web interaction with grounded language agents
Shunyu Yao, Howard Chen, John Yang, and Karthik Narasimhan. 2022 · 2022
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Prompting and evaluating large language models for proactive dialogues: Clarification, target-guided, and non-collaboration
Yang Deng, Lizi Liao, Liang Chen, Hongru Wang, Wenqiang Lei, and Tat-Seng Chua. 2023c · 2023
Cited alongside, same era.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2023 · 2023
Cited alongside, same era.
Proactive conversational agents in the post-chatgpt world
Lizi Liao, Grace Hui Yang, and Chirag Shah. 2023 · 2023
Cited alongside, same era.
ClarifyDelphi: Reinforced clarification questions with defeasibility rewards for social and moral situations
Valentina Pyatkin, Jena D. Hwang, Vivek Srikumar, Ximing Lu, Liwei Jiang, Yejin Choi, and Chandra Bhagavatula. 2023 · 2023
Cited alongside, same era.
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
Cited alongside, same era.
STYLE: improving domain transferability of asking clarification questions in large language model powered conversational agents
Yue Chen, Chen Huang, Yang Deng, Wenqiang Lei, Dingnan Jin, Jia Liu, and Tat-Seng Chua. 2024 · 2024
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Large language model powered agents in the web
Yang Deng, An Zhang, Yankai Lin, Xu Chen, Ji-Rong Wen, and Tat-Seng Chua. 2024a · 2024
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Tell me more! towards implicit user intention understanding of language model driven agents
Cheng Qian, Bingxiang He, Zhong Zhuang, Jia Deng, Yujia Qin, Xin Cong, Zhong Zhang, Jie Zhou, Yankai Lin, Zhiyuan Liu, and Maosong Sun. 2024 · 2024
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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, et al. 2024 · 2024
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Agentclinic: a multimodal agent benchmark to evaluate ai in simulated clinical environments
Samuel Schmidgall, Rojin Ziaei, Carl Harris, Eduardo Reis, Jeffrey Jopling, and Michael Moor. 2024 · 2024
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Reflexion: an autonomous agent with dynamic memory and self-reflection
Noah Shinn, Beck Labash, and Ashwin Gopinath. 2023 · 2023
Cited alongside, same era.
Dilu: A knowledge-driven approach to autonomous driving with large language models
Licheng Wen, Daocheng Fu, Xin Li, Xinyu Cai, Tao Ma, Pinlong Cai, Min Dou, Botian Shi, Liang He, and Yu Qiao. 2023 · 2023
Cited alongside, same era.
InSCIt: Information-seeking conversations with mixed-initiative interactions
Zeqiu Wu, Ryu Parish, Hao Cheng, Sewon Min, Prithviraj Ammanabrolu, Mari Ostendorf, and Hannaneh Hajishirzi. 2023 · 2023
Cited alongside, same era.
The rise and potential of large language model based agents: A survey
Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, et al. 2023 · 2023
Cited alongside, same era.
React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R Narasimhan, and Yuan Cao. 2023 · 2023
Cited alongside, same era.
Xizhou Zhu, Yuntao Chen, Hao Tian, Chenxin Tao, Weijie Su, Chenyu Yang, Gao Huang, Bin Li, Lewei Lu, Xiaogang Wang, et al. 2023 · 2023
Cited alongside, same era.
Star-gate: Teaching language models to ask clarifying questions
Chinmaya Andukuri, Jan-Philipp Fränken, Tobias Gerstenberg, and Noah D Goodman. 2024 · 2024
Cited alongside, same era.
Closest in time.
Adaptive in-conversation team building for language model agents
Linxin Song, Jiale Liu, Jieyu Zhang, Shaokun Zhang, Ao Luo, Shijian Wang, Qingyun Wu, and Chi Wang. 2024 · 2024
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Llms in the imaginarium: tool learning through simulated trial and error
Boshi Wang, Hao Fang, Jason Eisner, Benjamin Van Durme, and Yu Su. 2024 · 2024
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A human-like reasoning framework for multi-phases planning task with large language models
Chengxing Xie and Difan Zou. 2024 · 2024
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Travelplanner: A benchmark for real-world planning with language agents
Jian Xie, Kai Zhang, Jiangjie Chen, Tinghui Zhu, Renze Lou, Yuandong Tian, Yanghua Xiao, and Yu Su. 2024 · 2024
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Large language model powered agents for information retrieval
An Zhang, Yang Deng, Yankai Lin, Xu Chen, Ji-Rong Wen, and Tat-Seng Chua. 2024a · 2024
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Clamber: A benchmark of identifying and clarifying ambiguous information needs in large language models
Tong Zhang, Peixin Qin, Yang Deng, Chen Huang, Wenqiang Lei, Junhong Liu, Dingnan Jin, Hongru Liang, and Tat-Seng Chua. 2024b · 2024
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Memorybank: Enhancing large language models with long-term memory
Wanjun Zhong, Lianghong Guo, Qiqi Gao, He Ye, and Yanlin Wang. 2024 · 2024
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