A General Theoretical Paradigm to Understand Learning from Human
Preferences

A General Theoretical Paradigm to Understand Learning from Human Preferences

18 October 2023

Bilal Piot

Daniele Calandriello

Papers citing "A General Theoretical Paradigm to Understand Learning from Human Preferences"

15 / 415 papers shown

Title
Improving In-context Learning via Bidirectional Alignment Chengwei Qin Wenhan Xia Fangkai Jiao Chen Chen Yuchen Hu Bosheng Ding Shafiq R. Joty 35 7 0 28 Dec 2023
Preference as Reward, Maximum Preference Optimization with Importance Sampling Zaifan Jiang Xing Huang Chao Wei 22 2 0 27 Dec 2023
Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-Constraint Wei Xiong Hanze Dong Chen Ye Ziqi Wang Han Zhong Heng Ji Nan Jiang Tong Zhang OffRL 38 156 0 18 Dec 2023
Policy Optimization in RLHF: The Impact of Out-of-preference Data Ziniu Li Tian Xu Yang Yu 26 29 0 17 Dec 2023
On Diversified Preferences of Large Language Model Alignment Dun Zeng Yong Dai Pengyu Cheng Longyue Wang Tianhao Hu Wanshun Chen Nan Du Zenglin Xu ALM 30 16 0 12 Dec 2023
RLHF and IIA: Perverse Incentives Wanqiao Xu Shi Dong Xiuyuan Lu Grace Lam Zheng Wen Benjamin Van Roy 29 2 0 02 Dec 2023
Nash Learning from Human Feedback Rémi Munos Michal Valko Daniele Calandriello M. G. Azar Mark Rowland ... Nikola Momchev Olivier Bachem D. Mankowitz Doina Precup Bilal Piot 28 123 0 01 Dec 2023
A density estimation perspective on learning from pairwise human preferences Vincent Dumoulin Daniel D. Johnson Pablo Samuel Castro Hugo Larochelle Yann Dauphin 29 12 0 23 Nov 2023
Adversarial Preference Optimization: Enhancing Your Alignment via RM-LLM Game Pengyu Cheng Yifan Yang Jian Li Yong Dai Tianhao Hu Peixin Cao Nan Du Xiaolong Li 26 28 0 14 Nov 2023
Controlled Decoding from Language Models Sidharth Mudgal Jong Lee H. Ganapathy Yaguang Li Tao Wang ... Michael Collins Trevor Strohman Jilin Chen Alex Beutel Ahmad Beirami 32 69 0 25 Oct 2023
Chat Vector: A Simple Approach to Equip LLMs with Instruction Following and Model Alignment in New Languages Shih-Cheng Huang Pin-Zu Li Yu-Chi Hsu Kuang-Ming Chen Yu Tung Lin Shih-Kai Hsiao Richard Tzong-Han Tsai Hung-yi Lee MoMe 34 13 0 07 Oct 2023
Mitigating the Alignment Tax of RLHF Yong Lin Hangyu Lin Wei Xiong Shizhe Diao Zeming Zheng ... Han Zhao Nan Jiang Heng Ji Yuan Yao Tong Zhang MoMe CLL 29 63 0 12 Sep 2023
Let Me Teach You: Pedagogical Foundations of Feedback for Language Models Beatriz Borges Niket Tandon Tanja Kaser Antoine Bosselut 22 3 0 01 Jul 2023
Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation Xiaoyu Chen Han Zhong Zhuoran Yang Zhaoran Wang Liwei Wang 118 60 0 23 May 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 308 11,915 0 04 Mar 2022