PopAlign: Population-Level Alignment for Fair Text-to-Image Generation

28 June 2024

Papers citing "PopAlign: Population-Level Alignment for Fair Text-to-Image Generation"

6 / 6 papers shown

Title
Preference Optimization with Multi-Sample Comparisons Chaoqi Wang Zhuokai Zhao Chen Zhu Karthik Abinav Sankararaman Michal Valko ... Zhaorun Chen Madian Khabsa Yuxin Chen Hao Ma Sinong Wang 59 10 0 16 Oct 2024
Generalizing Alignment Paradigm of Text-to-Image Generation with Preferences through $f$ -divergence Minimization Haoyuan Sun Bo Xia Yongzhe Chang Xueqian Wang EGVM 35 2 0 15 Sep 2024
Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation Yuval Kirstain Adam Polyak Uriel Singer Shahbuland Matiana Joe Penna Omer Levy EGVM 163 345 0 02 May 2023
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 301 11,730 0 04 Mar 2022
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 253 4,735 0 24 Feb 2021
Improving the Fairness of Deep Generative Models without Retraining Shuhan Tan Yujun Shen Bolei Zhou 167 59 0 09 Dec 2020