Quantifying Bias in Text-to-Image Generative Models

20 December 2023

Papers citing "Quantifying Bias in Text-to-Image Generative Models"

7 / 7 papers shown

Title
Is What You Ask For What You Get? Investigating Concept Associations in Text-to-Image Models Salma Abdel Magid Weiwei Pan Simon Warchol Grace Guo Junsik Kim Mahia Rahman Hanspeter Pfister 84 0 0 06 Oct 2024
Social Biases through the Text-to-Image Generation Lens Ranjita Naik Besmira Nushi 91 111 0 30 Mar 2023
Bias Mimicking: A Simple Sampling Approach for Bias Mitigation Maan Qraitem Kate Saenko Bryan A. Plummer 46 33 0 30 Sep 2022
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation Models Jaemin Cho Abhaysinh Zala Mohit Bansal ViT 132 167 0 08 Feb 2022
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation Junnan Li Dongxu Li Caiming Xiong S. Hoi MLLM BDL VLM CLIP 382 4,010 0 28 Jan 2022
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 286 4,143 0 23 Aug 2019
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 279 39,083 0 01 Sep 2014