Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences

4 April 2024

Papers citing "Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences"

7 / 7 papers shown

Title
LiPO: Listwise Preference Optimization through Learning-to-Rank Tianqi Liu Zhen Qin Junru Wu Jiaming Shen Misha Khalman ... Mohammad Saleh Simon Baumgartner Jialu Liu Peter J. Liu Xuanhui Wang 101 37 0 28 Jan 2025
Reward-Augmented Data Enhances Direct Preference Alignment of LLMs Shenao Zhang Zhihan Liu Boyi Liu Y. Zhang Yingxiang Yang Y. Liu Liyu Chen Tao Sun Z. Wang 64 2 0 10 Oct 2024
KTO: Model Alignment as Prospect Theoretic Optimization Kawin Ethayarajh Winnie Xu Niklas Muennighoff Dan Jurafsky Douwe Kiela 139 147 0 02 Feb 2024
Self-Rewarding Language Models Weizhe Yuan Richard Yuanzhe Pang Kyunghyun Cho Xian Li Sainbayar Sukhbaatar Jing Xu Jason Weston ReLM SyDa ALM LRM 190 133 0 18 Jan 2024
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models Avi Singh John D. Co-Reyes Rishabh Agarwal Ankesh Anand Piyush Patil ... Yamini Bansal Ethan Dyer Behnam Neyshabur Jascha Narain Sohl-Dickstein Noah Fiedel ALM LRM ReLM SyDa 127 66 0 11 Dec 2023
Self-Consistency Improves Chain of Thought Reasoning in Language Models Xuezhi Wang Jason W. Wei Dale Schuurmans Quoc Le Ed H. Chi Sharan Narang Aakanksha Chowdhery Denny Zhou ReLM BDL LRM AI4CE 267 2,029 0 21 Mar 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 298 8,441 0 04 Mar 2022