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Large language models (LLMs) hold the promise of solving diverse tasks when provided with appropriate natural language prompts.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D 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 Ziegler, Jeffrey Wu, Clemens Winter, Chris 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
Earlier work this paper cites.
Trl: Transformer reinforcement learning
Leandro von Werra, Younes Belkada, Lewis Tunstall, Edward Beeching, Tristan Thrush, Nathan Lambert, and Shengyi Huang · 2020
Earlier work this paper cites.
Learning from task descriptions, 2020
Orion Weller, Nicholas Lourie, Matt Gardner, and Matthew E. Peters · 2020
Earlier work this paper cites.
Systematic inequalities in language technology performance across the world’s languages
Damián E. Blasi, Antonios Anastasopoulos, and Graham Neubig · 2021
Earlier work this paper cites.
Aggregating complex annotations via merging and matching
Alexander Braylan and Matthew Lease · 2021
Earlier work this paper cites.
Making pre-trained language models better few-shot learners
Tianyu Gao, Adam Fisch, and Danqi Chen · 2021
Earlier work this paper cites.
Balancing average and worst-case accuracy in multitask learning
Paul Michel, Sebastian Ruder, and Dani Yogatama · 2021
Earlier work this paper cites.
Unnatural instructions: Tuning language models with (almost) no human labor, 2022
Or Honovich, Thomas Scialom, Omer Levy, and Timo Schick · 2022
Earlier work this paper cites.
Illustrating reinforcement learning from human feedback (rlhf)
Nathan Lambert, Louis Castricato, Leandro von Werra, and Alex Havrilla · 2022
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Cross-lingual inference with a chinese entailment graph, 2022
Tianyi Li, Sabine Weber, Mohammad Javad Hosseini, Liane Guillou, and Mark Steedman · 2022
Earlier work this paper cites.
Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning
Haokun Liu, Derek Tam, Mohammed Muqeeth, Jay Mohta, Tenghao Huang, Mohit Bansal, and Colin Raffel · 2022
Earlier work this paper cites.
Cross-task generalization via natural language crowdsourcing instructions, 2022
Swaroop Mishra, Daniel Khashabi, Chitta Baral, and Hannaneh Hajishirzi · 2022
Earlier work this paper cites.
Training language models to follow instructions with human feedback, 2022
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe · 2022
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Super-naturalinstructions: Generalization via declarative instructions on 1600+ nlp tasks, 2022
Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi, Yeganeh Kordi, Amirreza Mirzaei, Anjana Arunkumar, Arjun Ashok, Arut Selvan Dhanasekaran, Atharva Naik, David Stap, Eshaan Pathak, Giannis Karamanolakis, Haizhi Gary Lai, Ishan Purohit, Ishani Mondal, Jacob Anderson, Kirby Kuznia, Krima Doshi, Maitreya Patel, Kuntal Kumar Pal, Mehrad Moradshahi, Mihir Parmar, Mirali Purohit, Neeraj Varshney, Phani Rohitha Kaza, Pulkit Verma, Ravsehaj Singh Puri, Rushang Karia, Shailaja Keyur Sampat, Savan Doshi, Siddhartha Mishra, Sujan Reddy, Sumanta Patro, Tanay Dixit, Xudong Shen, Chitta Baral, Yejin Choi, Noah A. Smith, Hannaneh Hajishirzi, and Daniel Khashabi · 2022
Earlier work this paper cites.
Finetuned language models are zero-shot learners, 2022
Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, and Quoc V. Le · 2022
Cited alongside, same era.
Limits and possibilities for “ethical ai” in open source: A study of deepfakes
David Gray Widder, Dawn Nafus, Laura A. Dabbish, and James D. Herbsleb · 2022
Cited alongside, same era.
Self-ICL: Zero-shot in-context learning with self-generated demonstrations
Wei-Lin Chen, Cheng-Kuang Wu, Yun-Nung Chen, and Hsin-Hsi Chen · 2023
Cited alongside, same era.
Teacherlm: Teaching to fish rather than giving the fish, language modeling likewise
Nan He, Hanyu Lai, Chenyang Zhao, Zirui Cheng, Junting Pan, Ruoyu Qin, Ruofan Lu, Rui Lu, Yunchen Zhang, Gangming Zhao, et al · 2023
Cited alongside, same era.
Trustgpt: A benchmark for trustworthy and responsible large language models
Judging llm-as-a-judge with mt-bench and chatbot arena, 2023
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica · 2023
Later among the works it cites.
Lima: Less is more for alignment, 2023
Chunting Zhou, Pengfei Liu, Puxin Xu, Srini Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, and Omer Levy · 2023
Later among the works it cites.
Internet of agents: Weaving a web of heterogeneous agents for collaborative intelligence
Weize Chen, Ziming You, Ran Li, Yitong Guan, Chen Qian, Chenyang Zhao, Cheng Yang, Ruobing Xie, Zhiyuan Liu, and Maosong Sun · 2024
Closest in time.
Chatbot arena: An open platform for evaluating llms by human preference, 2024
Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Hao Zhang, Banghua Zhu, Michael Jordan, Joseph E. Gonzalez, and Ion Stoica · 2024
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Yue Huang, Qihui Zhang, Lichao Sun, et al · 2023
Cited alongside, same era.
Label-assemble: Leveraging multiple datasets with partial labels
Mintong Kang, Bowen Li, Zengle Zhu, Yongyi Lu, Elliot K. Fishman, Alan Yuille, and Zongwei Zhou · 2023
Cited alongside, same era.
Dspy: Compiling declarative language model calls into self-improving pipelines, 2023
Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, Ashutosh Sharma, Thomas T. Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, and Christopher Potts · 2023
Cited alongside, same era.
Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, and Ion Stoica · 2023
Cited alongside, same era.
Self-alignment with instruction backtranslation, 2023
Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Luke Zettlemoyer, Omer Levy, Jason Weston, and Mike Lewis · 2023
Cited alongside, same era.
Code llama: Open foundation models for code
Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Tan, Yossi Adi, Jingyu Liu, Tal Remez, Jérémy Rapin, Artyom Kozhevnikov, I. Evtimov, Joanna Bitton, Manish P Bhatt, Cristian Cantón Ferrer, Aaron Grattafiori, Wenhan Xiong, Alexandre D’efossez, Jade Copet, Faisal Azhar, Hugo Touvron, Louis Martin, Nicolas Usunier, Thomas Scialom, and Gabriel Synnaeve · 2023
Cited alongside, same era.
Prompt2model: Generating deployable models from natural language instructions
Vijay Viswanathan, Chenyang Zhao, Amanda Bertsch, Tongshuang Wu, and Graham Neubig · 2023
Cited alongside, same era.
Self-instruct: Aligning language models with self-generated instructions, 2023
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, and Hannaneh Hajishirzi · 2023
Cited alongside, same era.
Xiaojing Fan and Chunliang Tao · 2024
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Training task experts through retrieval based distillation
Jiaxin Ge, Xueying Jia, Vijay Viswanathan, Hongyin Luo, and Graham Neubig · 2024
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Minicpm: Unveiling the potential of small language models with scalable training strategies
Shengding Hu, Yuge Tu, Xu Han, Chaoqun He, Ganqu Cui, Xiang Long, Zhi Zheng, Yewei Fang, Yuxiang Huang, Weilin Zhao, et al · 2024
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Datadreamer: A tool for synthetic data generation and reproducible llm workflows
Ajay Patel, Colin Raffel, and Chris Callison-Burch · 2024
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Fmint: Bridging human designed and data pretrained models for differential equation foundation model, 2024
Zezheng Song, Jiaxin Yuan, and Haizhao Yang · 2024
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Trustllm: Trustworthiness in large language models
Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, et al · 2024
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Efficient large language models: A survey, 2024
Zhongwei Wan, Xin Wang, Che Liu, Samiul Alam, Yu Zheng, Jiachen Liu, Zhongnan Qu, Shen Yan, Yi Zhu, Quanlu Zhang, Mosharaf Chowdhury, and Mi Zhang · 2024
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Gpt-signal: Generative ai for semi-automated feature engineering in the alpha research process
Yining Wang, Jinman Zhao, and Yuri Lawryshyn · 2024
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Exploring the limitations of large language models in compositional relation reasoning
Jinman Zhao and Xueyan Zhang · 2024
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Gender bias in large language models across multiple languages
Jinman Zhao, Yitian Ding, Chen Jia, Yining Wang, and Zifan Qian · 2024
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