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Reinforcement learning from human feedback (RLHF) is a vital strategy for enhancing model capability in language models.
Instruction induction: From few examples to natural language task descriptions
Or Honovich, Uri Shaham, Samuel R. Bowman, and Omer Levy. 2023 · 1952
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Chris J Kennedy, Geoff Bacon, Alexander Sahn, and Claudia von Vacano. 2020 · 2009
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Detecting suicidality on twitter
Bridianne O’Dea, Stephen Wan, Philip J. Batterham, Alison L. Calear, Cecile Paris, and Helen Christensen. 2015 · 2015
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SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Multi-class machine classification of suicide-related communication on twitter
Pete Burnap, Gualtiero Colombo, Rosie Amery, Andrei Hodorog, and Jonathan Scourfield. 2017 · 2017
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TriviaQA: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer. 2017 · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017
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QuAC: Question answering in context
Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang, and Luke Zettlemoyer. 2018 · 2018
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BoolQ: Exploring the surprising difficulty of natural yes/no questions
Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, and Kristina Toutanova. 2019 · 2019
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Natural questions: A benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M. Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov. 2019 · 2019
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HellaSwag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019 · 2019
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The pushshift reddit dataset
Jason Baumgartner, Savvas Zannettou, Brian Keegan, Megan Squire, and Jeremy Blackburn. 2020 · 2020
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Learning to summarize with human feedback
Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F Christiano. 2020 · 2020
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Josh Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, and Wojciech Zaremba. 2021 · 2021
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Training verifiers to solve math word problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman. 2021 · 2021
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A framework for few-shot language model evaluation
Leo Gao, Jonathan Tow, Stella Biderman, Sid Black, Anthony DiPofi, Charles Foster, Laurence Golding, Jeffrey Hsu, Kyle McDonell, Niklas Muennighoff, Jason Phang, Laria Reynolds, Eric Tang, Anish Thite, Ben Wang, Kevin Wang, and Andy Zou. 2021 · 2021
Cited alongside, same era.
Deep learning for suicide and depression identification with unsupervised label correction
Ayaan Haque, Viraaj Reddi, and Tyler Giallanza. 2021 · 2021
Cited alongside, same era.
Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2021 · 2021
Cited alongside, same era.
Winogrande: An adversarial winograd schema challenge at scale
Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2021 · 2021
Cited alongside, same era.
Directions in abusive language training data, a systematic review: Garbage in, garbage out
Bertie Vidgen and Leon Derczynski. 2021 · 2021
Cited alongside, same era.
Huggingface h4 stack exchange preference dataset
Nathan Lambert, Lewis Tunstall, Nazneen Rajani, and Tristan Thrush. 2023 · 2023
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Alpacaeval: An automatic evaluator of instruction-following models
Xuechen Li, Tianyi Zhang, Yann Dubois, Rohan Taori, Ishaan Gulrajani, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto. 2023 · 2023
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Llms as narcissistic evaluators: When ego inflates evaluation scores
Yiqi Liu, Nafise Sadat Moosavi, and Chenghua Lin. 2023 · 2023
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Instruction in the wild: A user-based instruction dataset
Jinjie Ni, Fuzhao Xue, Kabir Jain, Mahir Hitesh Shah, Zangwei Zheng, and Yang You. 2023 · 2023
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OpenAI. 2023 · 2023
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Deep Ganguli, Liane Lovitt, Jackson Kernion, Amanda Askell, Yuntao Bai, Saurav Kadavath, Ben Mann, Ethan Perez, Nicholas Schiefer, Kamal Ndousse, Andy Jones, Sam Bowman, Anna Chen, Tom Conerly, Nova DasSarma, Dawn Drain, Nelson Elhage, Sheer El-Showk, Stanislav Fort, Zac Hatfield-Dodds, Tom Henighan, Danny Hernandez, Tristan Hume, Josh Jacobson, Scott Johnston, Shauna Kravec, Catherine Olsson, Sam Ringer, Eli Tran-Johnson, Dario Amodei, Tom Brown, Nicholas Joseph, Sam McCandlish, Chris Olah, Jared Kaplan, and Jack Clark. 2022 · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
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 · 2022
Cited alongside, same era.
Impact of pretraining term frequencies on few-shot reasoning
Yasaman Razeghi, Robert L. Logan IV au2, Matt Gardner, and Sameer Singh. 2022 · 2022
Cited alongside, same era.
Saferdialogues: Taking feedback gracefully after conversational safety failures
Megan Ung, Jing Xu, and Y-Lan Boureau. 2022 · 2022
Cited alongside, same era.
Ultrafeedback: Boosting language models with high-quality feedback
Ganqu Cui, Lifan Yuan, Ning Ding, Guanming Yao, Wei Zhu, Yuan Ni, Guotong Xie, Zhiyuan Liu, and Maosong Sun. 2023 · 2023
Cited alongside, same era.
Safe rlhf: Safe reinforcement learning from human feedback
Josef Dai, Xuehai Pan, Ruiyang Sun, Jiaming Ji, Xinbo Xu, Mickel Liu, Yizhou Wang, and Yaodong Yang. 2023 · 2023
Cited alongside, same era.
How ready are pre-trained abstractive models and llms for legal case judgement summarization?
Aniket Deroy, Kripabandhu Ghosh, and Saptarshi Ghosh. 2023 · 2023
Cited alongside, same era.
Rafael Rafailov, Archit Sharma, Eric Mitchell, Stefano Ermon, Christopher D. Manning, and Chelsea Finn. 2023 · 2023
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Grounding or guesswork? large language models are presumptive grounders
Omar Shaikh, Kristina Gligorić, Ashna Khetan, Matthias Gerstgrasser, Diyi Yang, and Dan Jurafsky. 2023 · 2023
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Stanford alpaca: An instruction-following llama model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto. 2023 · 2023
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, and Denny Zhou. 2023 · 2023
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Wizardlm: Empowering large language models to follow complex instructions
Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, and Daxin Jiang. 2023 · 2023
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Shadow alignment: The ease of subverting safely-aligned language models
Xianjun Yang, Xiao Wang, Qi Zhang, Linda Petzold, William Yang Wang, Xun Zhao, and Dahua Lin. 2023 · 2023
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Guess the instruction! flipped learning makes language models stronger zero-shot learners
Seonghyeon Ye, Doyoung Kim, Joel Jang, Joongbo Shin, and Minjoon Seo. 2023 · 2023
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Judging LLM-as-a-judge with MT-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica. 2023 · 2023
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Large language models are human-level prompt engineers
Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, and Jimmy Ba. 2023 · 2023
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Self-alignment with instruction backtranslation
Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Omer Levy, Luke Zettlemoyer, Jason Weston, and Mike Lewis. 2024 · 2024
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