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Large language model (LLM) agents have demonstrated impressive capabilities in utilizing external tools and knowledge to boost accuracy and reduce hallucinations.
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2021 · 2005
Earlier work this paper cites.
Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models
Bryan A. Plummer, Liwei Wang, Chris M. Cervantes, Juan C. Caicedo, Julia Hockenmaier, and Svetlana Lazebnik. 2017 · 2017
Earlier work this paper cites.
HotpotQA: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W Cohen, Ruslan Salakhutdinov, and Christopher D Manning. 2018a · 2018
Earlier work this paper cites.
Retrieval augmented language model pre-training. In ICML . PMLR
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Mingwei Chang. 2020 · 2020
Earlier work this paper cites.
Dense Passage Retrieval for Open-Domain Question Answering. In EMNLP
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick S. H. Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
Earlier work this paper cites.
WebGPT: Browser-assisted question-answering with human feedback
Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Ouyang Long, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, Xu Jiang, Karl Cobbe, Tyna Eloundou, Gretchen Krueger, Kevin Button, Matthew Knight, Benjamin Chess, and John Schulman. 2021 · 2021
Earlier work this paper cites.
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
Michihiro Yasunaga, Hongyu Ren, Antoine Bosselut, Percy Liang, and Jure Leskovec. 2021 · 2021
Earlier work this paper cites.
Improving Language Models by Retrieving from Trillions of Tokens. In ICML
Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George van den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, Diego de Las Casas, Aurelia Guy, Jacob Menick, Roman Ring, Tom Hennigan, Saffron Huang, Loren Maggiore, Chris Jones, Albin Cassirer, Andy Brock, Michela Paganini, Geoffrey Irving, Oriol Vinyals, Simon Osindero, Karen Simonyan, Jack W. Rae, Erich Elsen, and Laurent Sifre. 2022 · 2022
Earlier work this paper cites.
RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning. In EMNLP . ACL
Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, Yihan Wang, Han Guo, Tianmin Shu, Meng Song, Eric P. Xing, and Zhiting Hu. 2022 · 2022
Earlier work this paper cites.
Efficient and effective training of language and graph neural network models
Vassilis N Ioannidis, Xiang Song, Da Zheng, Houyu Zhang, Jun Ma, Yi Xu, Belinda Zeng, Trishul Chilimbi, and George Karypis. 2022 · 2022
Earlier work this paper cites.
CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning. In NeurIPS
Hung Le, Yue Wang, Akhilesh Deepak Gotmare, Silvio Savarese, and Steven Chu-Hong Hoi. 2022 · 2022
Earlier work this paper cites.
TALM: Tool Augmented Language Models
Aaron Parisi, Yao Zhao, and Noah Fiedel. 2022 · 2022
Earlier work this paper cites.
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. In NeurIPS
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, and Denny Zhou. 2022 · 2022
Earlier work this paper cites.
Teaching Large Language Models to Self-Debug
Xinyun Chen, Maxwell Lin, Nathanael Schärli, and Denny Zhou. 2023a · 2023
Earlier work this paper cites.
Large language models are zero-shot rankers for recommender systems
Yupeng Hou, Junjie Zhang, Zihan Lin, Hongyu Lu, Ruobing Xie, Julian McAuley, and Wayne Xin Zhao. 2023 · 2023
Earlier work this paper cites.
Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP
Omar Khattab, Keshav Santhanam, Xiang Lisa Li, David Hall, Percy Liang, Christopher Potts, and Matei Zaharia. 2023 · 2023
Earlier work this paper cites.
CAMEL: Communicative Agents for "Mind" Exploration of Large Scale Language Model Society
Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, Dmitrii Khizbullin, and Bernard Ghanem. 2023a · 2023
Earlier work this paper cites.
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, Shudan Zhang, Xiang Deng, Aohan Zeng, Zhengxiao Du, Chenhui Zhang, Sheng Shen, Tianjun Zhang, Yu Su, Huan Sun, Minlie Huang, Yuxiao Dong, and Jie Tang. 2023 · 2023
Earlier work this paper cites.
Hierarchical Prompting Assists Large Language Model on Web Navigation. In Findings of the Association for Computational Linguistics: EMNLP 2023
Robert Lo, Abishek Sridhar, Frank Xu, Hao Zhu, and Shuyan Zhou. 2023 · 2023
Cited alongside, same era.
Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models. In NeurIPS
Pan Lu, Baolin Peng, Hao Cheng, Michel Galley, Kai-Wei Chang, Ying Nian Wu, Song-Chun Zhu, and Jianfeng Gao. 2023 · 2023
Cited alongside, same era.
Self-Refine: Iterative Refinement with Self-Feedback. In NeurIPS
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, and Peter Clark. 2023 · 2023
Cited alongside, same era.
MemGPT: Towards LLMs as Operating Systems
Charles Packer, Vivian Fang, Shishir G. Patil, Kevin Lin, Sarah Wooders, and Joseph E. Gonzalez. 2023 · 2023
Cited alongside, same era.
ART: Automatic multi-step reasoning and tool-use for large language models
Outline, then details: Syntactically guided coarse-to-fine code generation
Wenqing Zheng, SP Sharan, Ajay Kumar Jaiswal, Kevin Wang, Yihan Xi, Dejia Xu, and Zhangyang Wang. 2023 · 2023
Later among the works it cites.
Large Language Models are Human-Level Prompt Engineers. In ICLR
Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, and Jimmy Ba. 2023 · 2023
Later among the works it cites.
Large language models for information retrieval: A survey
Yutao Zhu, Huaying Yuan, Shuting Wang, Jiongnan Liu, Wenhan Liu, Chenlong Deng, Zhicheng Dou, and Ji-Rong Wen. 2023 · 2023
Later among the works it cites.
Yao Fu, Dong-Ki Kim, Jaekyeom Kim, Sungryull Sohn, Lajanugen Logeswaran, Kyunghoon Bae, and Honglak Lee. 2024 · 2024
Closest in time.
Inductive reasoning in humans and large language models
Simon Jerome Han, Keith J. Ransom, Andrew Perfors, and Charles Kemp. 2024 · 2024
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Bhargavi Paranjape, Scott Lundberg, Sameer Singh, Hannaneh Hajishirzi, Luke Zettlemoyer, and Marco Tulio Ribeiro. 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.
Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback
Baolin Peng, Michel Galley, Pengcheng He, Hao Cheng, Yujia Xie, Yu Hu, Qiuyuan Huang, Lars Liden, Zhou Yu, Weizhu Chen, and Jianfeng Gao. 2023 · 2023
Cited alongside, same era.
WebCPM: Interactive Web Search for Chinese Long-form Question Answering. In Proceedings of ACL 2023 . Association for Computational Linguistics
Yujia Qin, Zihan Cai, Dian Jin, Lan Yan, Shihao Liang, Kunlun Zhu, Yankai Lin, Xu Han, Ning Ding, Huadong Wang, Ruobing Xie, Fanchao Qi, Zhiyuan Liu, Maosong Sun, and Jie Zhou. 2023a · 2023
Cited alongside, same era.
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, Runchu Tian, Ruobing Xie, Jie Zhou, Mark Gerstein, Dahai Li, Zhiyuan Liu, and Maosong Sun. 2023b · 2023
Cited alongside, same era.
Toolformer: Language Models Can Teach Themselves to Use Tools. In NeurIPS
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.
HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face. In NeurIPS
Yongliang Shen, Kaitao Song, Xu Tan, Dongsheng Li, Weiming Lu, and Yueting Zhuang. 2023 · 2023
Cited alongside, same era.
Reflexion: language agents with verbal reinforcement learning. In NeurIPS
Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao. 2023 · 2023
Cited alongside, same era.
Closest in time.
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering
Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh V. Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, and Bryan Hooi. 2024 · 2024
Closest in time.
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 · 2024
Closest in time.
Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models. In ACL
Lei Li, Yuqi Wang, Runxin Xu, Peiyi Wang, Xiachong Feng, Lingpeng Kong, and Qi Liu. 2024 · 2024
Closest in time.
Wenqi Shi, Ran Xu, Yuchen Zhuang, Yue Yu, Jieyu Zhang, Hang Wu, Yuanda Zhu, Joyce Ho, Carl Yang, and May D Wang. 2024 · 2024
Closest in time.
Hypothesis Search: Inductive Reasoning with Language Models
Ruocheng Wang, Eric Zelikman, Gabriel Poesia, Yewen Pu, Nick Haber, and Noah D. Goodman. 2024 · 2024
Closest in time.
STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases
Shirley Wu, Shiyu Zhao, Michihiro Yasunaga, Kexin Huang, Kaidi Cao, Qian Huang, Vassilis N. Ioannidis, Karthik Subbian, James Zou, and Jure Leskovec. 2024 · 2024
Closest in time.
Large Language Models as Optimizers
Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V. Le, Denny Zhou, and Xinyun Chen. 2024 · 2024
Closest in time.
Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization
Weiran Yao, Shelby Heinecke, Juan Carlos Niebles, Zhiwei Liu, Yihao Feng, Le Xue, Rithesh Murthy, Zeyuan Chen, Jianguo Zhang, Devansh Arpit, Ran Xu, Phil Mui, Huan Wang, Caiming Xiong, and Silvio Savarese. 2024 · 2024
Closest in time.
Junjie Ye, Guanyu Li, Songyang Gao, Caishuang Huang, Yilong Wu, Sixian Li, Xiaoran Fan, Shihan Dou, Qi Zhang, Tao Gui, and Xuanjing Huang. 2024 · 2024
Closest in time.
Training Language Model Agents without Modifying Language Models
Shaokun Zhang, Jieyu Zhang, Jiale Liu, Linxin Song, Chi Wang, Ranjay Krishna, and Qingyun Wu. 2024 · 2024
Closest in time.
ExpeL: LLM Agents Are Experiential Learners. In AAAI
Andrew Zhao, Daniel Huang, Quentin Xu, Matthieu Lin, Yong-Jin Liu, and Gao Huang. 2024 · 2024
Closest in time.
MemoryBank: Enhancing Large Language Models with Long-Term Memory. In AAAI
Wanjun Zhong, Lianghong Guo, Qiqi Gao, He Ye, and Yanlin Wang. 2024 · 2024
Closest in time.