{"total":20,"rows":[{"id":"2303.07909","title":"Text-to-image Diffusion Models in Generative AI: A Survey","created":"2023-03-14","cited_by_count":265,"area":"diffusion"},{"id":"2311.07604","title":"Finetuning Text-to-Image Diffusion Models for Fairness","created":"2023-11-11","cited_by_count":92,"area":"diffusion"},{"id":"2305.11080","title":"Inspecting the Geographical Representativeness of Images from Text-to-Image Models","created":"2023-05-18","cited_by_count":44,"area":"diffusion"},{"id":"2305.13308","title":"If at First You Don't Succeed, Try, Try Again: Faithful Diffusion-based Text-to-Image Generation by Selection","created":"2023-05-22","cited_by_count":40,"area":"diffusion"},{"id":"2311.17695","title":"Fair Text-to-Image Diffusion via Fair Mapping","created":"2023-11-29","cited_by_count":31,"area":"diffusion"},{"id":"2408.12692","title":"Rethinking Training for De-biasing Text-to-Image Generation: Unlocking the Potential of Stable Diffusion","created":"2024-08-22","cited_by_count":22,"area":"diffusion"},{"id":"2411.16171","title":"Image Generation Diversity Issues and How to Tame Them","created":"2024-11-25","cited_by_count":22,"area":"diffusion"},{"id":"2310.12583","title":"Diverse Diffusion: Enhancing Image Diversity in Text-to-Image Generation","created":"2023-10-19","cited_by_count":8,"area":"diffusion"},{"id":"2401.14425","title":"No Longer Trending on Artstation: Prompt Analysis of Generative AI Art","created":"2024-01-24","cited_by_count":7,"area":"diffusion"},{"id":"2502.16902","title":"Culture-TRIP: Culturally-Aware Text-to-Image Generation with Iterative Prompt Refinement","created":"2025-02-24","cited_by_count":7,"area":"diffusion"},{"id":"2503.01872","title":"FairGen: Controlling Sensitive Attributes for Fair Generations in Diffusion Models via Adaptive Latent Guidance","created":"2025-02-25","cited_by_count":7,"area":"diffusion"},{"id":"2510.21363","title":"FairImagen: Post-Processing for Bias Mitigation in Text-to-Image Models","created":"2025-10-24","cited_by_count":7,"area":"diffusion"},{"id":"2409.18214","title":"Trustworthy Text-to-Image Diffusion Models: A Timely and Focused Survey","created":"2024-09-26","cited_by_count":6,"area":"diffusion"},{"id":"2412.00580","title":"Continuous Concepts Removal in Text-to-image Diffusion Models","created":"2024-11-30","cited_by_count":6,"area":"diffusion"},{"id":"2412.01339","title":"Negative Token Merging: Image-based Adversarial Feature Guidance","created":"2024-12-02","cited_by_count":4,"area":"diffusion"},{"id":"2501.15775","title":"Do Existing Testing Tools Really Uncover Gender Bias in Text-to-Image Models?","created":"2025-01-27","cited_by_count":4,"area":"diffusion"},{"id":"2601.20791","title":"FAIRT2V: Training-Free Debiasing for Text-to-Video Diffusion Models","created":"2026-01-28","cited_by_count":1,"area":"diffusion"},{"id":"2604.21036","title":"Who Defines Fairness? Target-Based Prompting for Demographic Representation in Generative Models","created":"2026-04-22","cited_by_count":1,"area":"diffusion"},{"id":"2607.00817","title":"Training-Free Debiasing of Diffusion Models via CLIP-Guided Denoising Optimization","created":"2026-07-01","cited_by_count":1,"area":"diffusion"},{"id":"2507.15663","title":"SustainDiffusion: Optimising the Social and Environmental Sustainability of Stable Diffusion Models","created":"2025-07-21","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}