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Varied approaches for aligning language models have been proposed, including supervised fine-tuning, RLHF, and direct optimization methods such as DPO.
A sequential algorithm for training text classifiers
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Training a helpful and harmless assistant with reinforcement learning from human feedback
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Kawin Ethayarajh, Yejin Choi, and Swabha Swayamdipta · 2022
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Training language models to follow instructions with human feedback
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Zhisong Zhang, Emma Strubell, and Eduard Hovy · 2022
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A general theoretical paradigm to understand learning from human preferences
Mohammad Gheshlaghi Azar, Mark Rowland, Bilal Piot, Daniel Guo, Daniele Calandriello, Michal Valko, and Rémi Munos · 2023
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Camels in a changing climate: Enhancing LM adaptation with Tulu 2
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SLiC-HF: Sequence likelihood calibration with human feedback
Yao Zhao, Rishabh Joshi, Tianqi Liu, Misha Khalman, Mohammad Saleh, and Peter J Liu · 2023
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Back to basics: Revisiting REINFORCE style optimization for learning from human feedback in LLMs
Arash Ahmadian, Chris Cremer, Matthias Gallé, Marzieh Fadaee, Julia Kreutzer, Ahmet Üstün, and Sara Hooker · 2024
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Human alignment of large language models through online preference optimisation
Daniele Calandriello, Daniel Guo, Rémi Munos, Mark Rowland, Yunhao Tang, Bernardo Ávila Pires, Pierre H. Richemond, Charline Le Lan, Michal Valko, Tianqi Liu, Rishabh Joshi, Zeyu Zheng, and Bilal Piot · 2024
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Provably sample efficient rlhf via active preference optimization
Nirjhar Das, Souradip Chakraborty, Aldo Pacchiano, and Sayak Ray Chowdhury · 2024
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Policy optimization in RLHF: The impact of out-of-preference data
Ziniu Li, Tian Xu, and Yang Yu · 2023
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Statistical rejection sampling improves preference optimization
Tianqi Liu, Yao Zhao, Rishabh Joshi, Misha Khalman, Mohammad Saleh, Peter J Liu, and Jialu Liu · 2023
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The generalization gap in offline reinforcement learning
Ishita Mediratta, Qingfei You, Minqi Jiang, and Roberta Raileanu · 2023
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Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn · 2023
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A Long Way to Go: Investigating Length Correlations in RLHF
Prasann Singhal, Tanya Goyal, Jiacheng Xu, and Greg Durrett · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
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Zephyr: Direct distillation of LM alignment
Lewis Tunstall, Edward Beeching, Nathan Lambert, Nazneen Rajani, Kashif Rasul, Younes Belkada, Shengyi Huang, Leandro von Werra, Clémentine Fourrier, Nathan Habib, et al · 2023
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Length-Corrected AlpacaEval: A Simple Debiasing of Automatic Evaluators
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Efficient exploration for LLMs
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KTO: Model alignment as prospect theoretic optimization
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Direct language model alignment from online AI feedback
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ORPO: Monolithic preference optimization without reference model
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RewardBench: Evaluating reward models for language modeling
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Aligning large language models by on-policy self-judgment
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