Cover Image

Intriguing Properties of Data Attribution on Diffusion Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zheng, Xiaosen, Pang, Tianyu, Du, Chao, Jiang, Jing, Lin, Min
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On Memorization in Diffusion Models
by: Gu, Xiangming, et al.
Published: (2023)

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

Intriguing Equivalence Structures of the Embedding Space of Vision Transformers
by: Salman, Shaeke, et al.
Published: (2024)

Intriguing Differences Between Zero-Shot and Systematic Evaluations of Vision-Language Transformer Models
by: Salman, Shaeke, et al.
Published: (2024)

Intriguing properties of generative classifiers
by: Jaini, Priyank, et al.
Published: (2023)

Cheating Automatic LLM Benchmarks: Null Models Achieve High Win Rates
by: Zheng, Xiaosen, et al.
Published: (2024)

Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses
by: Zheng, Xiaosen, et al.
Published: (2024)

Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast
by: Gu, Xiangming, et al.
Published: (2024)

DMin: Scalable Training Data Influence Estimation for Diffusion Models
by: Lin, Huawei, et al.
Published: (2024)

Attribution-Guided Model Rectification of Unreliable Neural Network Behaviors
by: Yang, Peiyu, et al.
Published: (2026)

Attributing Data for Sharpness-Aware Minimization
by: Ren, Chenyang, et al.
Published: (2025)

Rethinking Diffusion Model in High Dimension
by: Zheng, Zhenxin, et al.
Published: (2025)

Nonparametric Data Attribution for Diffusion Models
by: Zhao, Yutian, et al.
Published: (2025)

Intriguing Properties of Modern GANs
by: Friedman, Roy, et al.
Published: (2024)

FairGen: Controlling Sensitive Attributes for Fair Generations in Diffusion Models via Adaptive Latent Guidance
by: Kang, Mintong, et al.
Published: (2025)

TurboDiffusion: Accelerating Video Diffusion Models by 100-200 Times
by: Zhang, Jintao, et al.
Published: (2025)

Towards Attributions of Input Variables in a Coalition
by: Zheng, Xinhao, et al.
Published: (2023)

Diffusion Model with Perceptual Loss
by: Lin, Shanchuan, et al.
Published: (2023)

Large-scale Reinforcement Learning for Diffusion Models
by: Zhang, Yinan, et al.
Published: (2024)

Training Diffusion Models with Reinforcement Learning
by: Black, Kevin, et al.
Published: (2023)

Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective
by: Liang, Yingyu, et al.
Published: (2024)

Heterogeneous Decentralized Diffusion Models
by: Jiang, Zhiying, et al.
Published: (2026)

From Baselines to Transport Geodesics: Axiomatic Attribution via Optimal Generative Flows
by: Zhang, Cenwei, et al.
Published: (2026)

Rethinking the Diffusion Model from a Langevin Perspective
by: Zheng, Candi, et al.
Published: (2026)

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation
by: Monsefi, Amin Karimi, et al.
Published: (2025)

Autoguided Online Data Curation for Diffusion Model Training
by: Pais, Valeria, et al.
Published: (2025)

SG-OIF: A Stability-Guided Online Influence Framework for Reliable Vision Data
by: Rao, Penghao, et al.
Published: (2025)

Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data
by: Daras, Giannis, et al.
Published: (2024)

Meta-Unlearning on Diffusion Models: Preventing Relearning Unlearned Concepts
by: Gao, Hongcheng, et al.
Published: (2024)

SPIE: Semantic and Structural Post-Training of Image Editing Diffusion Models with AI feedback
by: Benarous, Elior, et al.
Published: (2025)

Fast Training of Diffusion Models with Masked Transformers
by: Zheng, Hongkai, et al.
Published: (2023)

Tree of Attributes Prompt Learning for Vision-Language Models
by: Ding, Tong, et al.
Published: (2024)

Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data
by: Aali, Asad, et al.
Published: (2024)

Inference-Time Scaling of Diffusion Models for Infrared Data Generation
by: Horstmann, Kai A., et al.
Published: (2025)

Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models
by: Wu, Xiaoyu, et al.
Published: (2024)

TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models
by: Huang, Yushi, et al.
Published: (2023)

Explaining Black-box Model Predictions via Two-level Nested Feature Attributions with Consistency Property
by: Yoshikawa, Yuya, et al.
Published: (2024)

Feature Attribution Stability Suite: How Stable Are Post-Hoc Attributions?
by: Subramaniakuppusamy, Kamalasankari, et al.
Published: (2026)

Taming Diffusion for Dataset Distillation with High Representativeness
by: Zhao, Lin, et al.
Published: (2025)

AAPL: Adding Attributes to Prompt Learning for Vision-Language Models
by: Kim, Gahyeon, et al.
Published: (2024)