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Large language models (LLMs) fine-tuned with reinforcement learning from human feedback (RLHF) have been used in some of the most widely deployed AI models to date, such as OpenAI's ChatGPT or Anthropic's Claude.
Fine-Tuning Language Models from Human Preferences, 2020
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Language models are few-shot learners
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A distributional approach to controlled text generation
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Evaluating the evaluation of diversity in natural language generation
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Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
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Robust Preference Learning for Storytelling via Contrastive Reinforcement Learning, 2022
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PaLM: Scaling Language Modeling with Pathways, 2022
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Introducing Claude, 2023
Anthropic · 2023
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Training Compute-Optimal Large Language Models, 2022
Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, Tom Hennigan, Eric Noland, Katie Millican, George van den Driessche, Bogdan Damoc, Aurelia Guy, Simon Osindero, Karen Simonyan, Erich Elsen, Jack W. Rae, Oriol Vinyals, and Laurent Sifre · 2022
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Mysteries of mode collapse, 2022
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Emergent autonomous scientific research capabilities of large language models, 2023
Daniil A. Boiko, Robert MacKnight, and Gabe Gomes · 2023
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Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback, 2023
Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Wang, Samuel Marks, Charbel-Raphaël Segerie, Micah Carroll, Andi Peng, Phillip Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Bıyık, Anca Dragan, David Krueger, Dorsa Sadigh, and Dylan Hadfield-Menell · 2023
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AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback, 2023
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Reinforcement Learning for Language Models, 2023
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OpenAssistant Conversations – Democratizing Large Language Model Alignment, 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
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GPTEval: A Survey on Assessments of ChatGPT and GPT-4, 2023
Rui Mao, Guanyi Chen, Xulang Zhang, Frank Guerin, and Erik Cambria · 2023
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OpenAI · 2023
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Instruction Tuning with GPT-4, 2023
Baolin Peng, Chunyuan Li, Pengcheng He, Michel Galley, and Jianfeng Gao · 2023
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Direct Preference Optimization: Your Language Model is Secretly a Reward Model, 2023
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Training Language Models with Language Feedback at Scale, 2023
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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
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RRHF: Rank Responses to Align Language Models with Human Feedback without tears, 2023
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The Wisdom of Hindsight Makes Language Models Better Instruction Followers, 2023
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