Cover Image

Debiasing Diffusion Model: Enhancing Fairness through Latent Representation Learning in Stable Diffusion Model

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Huang, Lin-Chun, Tsao, Ching Chieh, Su, Fang-Yi, Chiang, Jung-Hsien
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computer Vision and Pattern Recognition Computers and Society
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Finetuning Text-to-Image Diffusion Models for Fairness
by: Shen, Xudong, et al.
Published: (2023)

FairDiffusion: Enhancing Equity in Latent Diffusion Models via Fair Bayesian Perturbation
by: Luo, Yan, et al.
Published: (2024)

SGD-Mix: Enhancing Domain-Specific Image Classification with Label-Preserving Data Augmentation
by: Dong, Yixuan, et al.
Published: (2025)

Prompting4Debugging: Red-Teaming Text-to-Image Diffusion Models by Finding Problematic Prompts
by: Chin, Zhi-Yi, et al.
Published: (2023)

Fair Text-to-Image Diffusion via Fair Mapping
by: Li, Jia, et al.
Published: (2023)

Fair Sampling in Diffusion Models through Switching Mechanism
by: Choi, Yujin, et al.
Published: (2024)

Replication in Visual Diffusion Models: A Survey and Outlook
by: Wang, Wenhao, et al.
Published: (2024)

The Evolving Nature of Latent Spaces: From GANs to Diffusion
by: Schaerf, Ludovica
Published: (2025)

FairFedMed: Benchmarking Group Fairness in Federated Medical Imaging with FairLoRA
by: Li, Minghan, et al.
Published: (2025)

AXOLOTL: Fairness through Assisted Self-Debiasing of Large Language Model Outputs
by: Ebrahimi, Sana, et al.
Published: (2024)

Debiasing Classifiers by Amplifying Bias with Latent Diffusion and Large Language Models
by: Ko, Donggeun, et al.
Published: (2024)

Debiasing Text-to-Image Diffusion Models
by: He, Ruifei, et al.
Published: (2024)

FairGen: Enhancing Fairness in Text-to-Image Diffusion Models via Self-Discovering Latent Directions
by: Jiang, Yilei, et al.
Published: (2024)

Stable Signer: Hierarchical Sign Language Generative Model
by: Fang, Sen, et al.
Published: (2025)

Warm Diffusion: Recipe for Blur-Noise Mixture Diffusion Models
by: Hsueh, Hao-Chien, et al.
Published: (2025)

Attention to Neural Plagiarism: Diffusion Models Can Plagiarize Your Copyrighted Images!
by: Zou, Zihang, et al.
Published: (2026)

Towards Reliable Verification of Unauthorized Data Usage in Personalized Text-to-Image Diffusion Models
by: Li, Boheng, et al.
Published: (2024)

Mass Concept Erasure in Diffusion Models with Concept Hierarchy
by: Tu, Jiahang, et al.
Published: (2026)

Zero-shot Adaptation of Stable Diffusion via Plug-in Hierarchical Degradation Representation for Real-World Super-Resolution
by: Liao, Yi-Cheng, et al.
Published: (2025)

Aggregate Representation Measure for Predictive Model Reusability
by: Sangarya, Vishwesh, et al.
Published: (2024)

Landscape-Awareness for Geometric View Diffusion Model
by: Chen, Yan-Ting, et al.
Published: (2026)

Data Augmentation via Diffusion Model to Enhance AI Fairness
by: Blow, Christina Hastings, et al.
Published: (2024)

StableGuard: Towards Unified Copyright Protection and Tamper Localization in Latent Diffusion Models
by: Yang, Haoxin, et al.
Published: (2025)

Debiasing Graph Representation Learning based on Information Bottleneck
by: Zhang, Ziyi, et al.
Published: (2024)

INFELM: In-depth Fairness Evaluation of Large Text-To-Image Models
by: Jin, Di, et al.
Published: (2024)

Isometric Representation Learning for Disentangled Latent Space of Diffusion Models
by: Hahm, Jaehoon, et al.
Published: (2024)

Energy Scaling Laws for Diffusion Models: Quantifying Compute in Image Generation
by: Iyengar, Aniketh, et al.
Published: (2025)

The Illusion of Forgetting: Attack Unlearned Diffusion via Initial Latent Variable Optimization
by: Li, Manyi, et al.
Published: (2026)

Canonical Latent Representations in Conditional Diffusion Models
by: Xu, Yitao, et al.
Published: (2025)

Balancing Act: Distribution-Guided Debiasing in Diffusion Models
by: Parihar, Rishubh, et al.
Published: (2024)

FairDD: Enhancing Fairness with domain-incremental learning in dermatological disease diagnosis
by: Luo, Yiqin, et al.
Published: (2024)

Debiasing Methods for Fairer Neural Models in Vision and Language Research: A Survey
by: Parraga, Otávio, et al.
Published: (2022)

Provable Optimization for Adversarial Fair Self-supervised Contrastive Learning
by: Qi, Qi, et al.
Published: (2024)

From Discrete to Continuous: Deep Fair Clustering With Transferable Representations
by: Zhang, Xiang
Published: (2024)

Face4FairShifts: A Large Image Benchmark for Fairness and Robust Learning across Visual Domains
by: Lin, Yumeng, et al.
Published: (2025)

An AI-Enabled Framework Within Reach for Enhancing Healthcare Sustainability and Fairness
by: Huang, Bin, et al.
Published: (2024)

A Cat Is A Cat (Not A Dog!): Unraveling Information Mix-ups in Text-to-Image Encoders through Causal Analysis and Embedding Optimization
by: Chen, Chieh-Yun, et al.
Published: (2024)

Beyond the Noise: Aligning Prompts with Latent Representations in Diffusion Models
by: Ramos, Vasco, et al.
Published: (2025)

Boosting Latent Diffusion Models via Disentangled Representation Alignment
by: Page, John, et al.
Published: (2026)

FairDD: Fair Dataset Distillation
by: Zhou, Qihang, et al.
Published: (2024)