OPTune: Efficient Online Preference Tuning

OPTune: Efficient Online Preference Tuning

11 June 2024

John Kirchenbauer

Tom Goldstein

Heng Huang

Papers citing "OPTune: Efficient Online Preference Tuning"

5 / 5 papers shown

Title
A Survey on Progress in LLM Alignment from the Perspective of Reward Design Miaomiao Ji Yanqiu Wu Zhibin Wu Shoujin Wang Jian Yang Mark Dras Usman Naseem 37 0 0 05 May 2025
RewardBench: Evaluating Reward Models for Language Modeling Nathan Lambert Valentina Pyatkin Jacob Morrison Lester James Validad Miranda Bill Yuchen Lin ... Sachin Kumar Tom Zick Yejin Choi Noah A. Smith Hanna Hajishirzi ALM 74 210 0 20 Mar 2024
KTO: Model Alignment as Prospect Theoretic Optimization Kawin Ethayarajh Winnie Xu Niklas Muennighoff Dan Jurafsky Douwe Kiela 159 437 0 02 Feb 2024
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 303 11,730 0 04 Mar 2022
Fine-Tuning Language Models from Human Preferences Daniel M. Ziegler Nisan Stiennon Jeff Wu Tom B. Brown Alec Radford Dario Amodei Paul Christiano G. Irving ALM 275 1,561 0 18 Sep 2019