{"total":28,"rows":[{"id":"2301.13188","title":"Extracting Training Data from Diffusion Models","created":"2023-01-30","cited_by_count":732,"area":"diffusion"},{"id":"2303.07345","title":"Erasing Concepts from Diffusion Models","created":"2023-03-13","cited_by_count":539,"area":"diffusion"},{"id":"2212.03860","title":"Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models","created":"2022-12-07","cited_by_count":424,"area":"diffusion"},{"id":"2303.13516","title":"Ablating Concepts in Text-to-Image Diffusion Models","created":"2023-03-23","cited_by_count":317,"area":"diffusion"},{"id":"2305.20086","title":"Understanding and Mitigating Copying in Diffusion Models","created":"2023-05-31","cited_by_count":209,"area":"diffusion"},{"id":"2310.02664","title":"On Memorization in Diffusion Models","created":"2023-10-04","cited_by_count":125,"area":"diffusion"},{"id":"2311.01797","title":"On the Generalization Properties of Diffusion Models","created":"2023-11-03","cited_by_count":68,"area":"diffusion"},{"id":"2403.11052","title":"Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention","created":"2024-03-17","cited_by_count":58,"area":"diffusion"},{"id":"2401.05779","title":"Erasing Undesirable Influence in Diffusion Models","created":"2024-01-11","cited_by_count":57,"area":"diffusion"},{"id":"2406.02366","title":"Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models","created":"2024-06-04","cited_by_count":37,"area":"diffusion"},{"id":"2405.16534","title":"Pruning for Robust Concept Erasing in Diffusion Models","created":"2024-05-26","cited_by_count":22,"area":"diffusion"},{"id":"2307.16680","title":"On the Trustworthiness Landscape of State-of-the-art Generative Models: A Survey and Outlook","created":"2023-07-31","cited_by_count":15,"area":"diffusion"},{"id":"2406.18566","title":"Memorized Images in Diffusion Models share a Subspace that can be Located and Deleted","created":"2024-06-01","cited_by_count":13,"area":"diffusion"},{"id":"2404.06737","title":"Disguised Copyright Infringement of Latent Diffusion Models","created":"2024-04-10","cited_by_count":10,"area":"diffusion"},{"id":"2410.02467","title":"SIDE: Surrogate Conditional Data Extraction from Diffusion Models","created":"2024-10-03","cited_by_count":7,"area":"diffusion"},{"id":"2405.05846","title":"An Inversion-based Measure of Memorization for Diffusion Models","created":"2024-05-09","cited_by_count":6,"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":"2504.18032","title":"Enhancing Privacy-Utility Trade-offs to Mitigate Memorization in Diffusion Models","created":"2025-04-25","cited_by_count":5,"area":"diffusion"},{"id":"2509.13046","title":"MIA-EPT: Membership Inference Attack via Error Prediction for Tabular Data","created":"2025-09-16","cited_by_count":4,"area":"diffusion"},{"id":"2410.16657","title":"Dual-Model Defense: Safeguarding Diffusion Models from Membership Inference Attacks through Disjoint Data Splitting","created":"2024-10-22","cited_by_count":3,"area":"diffusion"},{"id":"2506.00849","title":"Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis","created":"2025-06-01","cited_by_count":3,"area":"diffusion"},{"id":"2603.02333","title":"Characterizing Memorization in Diffusion Language Models: Generalized Extraction and Sampling Effects","created":"2026-03-02","cited_by_count":3,"area":"diffusion"},{"id":"2604.10032","title":"Closed-Form Concept Erasure via Double Projections","created":"2026-04-11","cited_by_count":3,"area":"diffusion"},{"id":"2603.00140","title":"Steering Away from Memorization: Reachability-Constrained Reinforcement Learning for Text-to-Image Diffusion","created":"2026-02-24","cited_by_count":1,"area":"diffusion"},{"id":"2605.30642","title":"Diffusion Models Preferentially Memorize Prototypical Examples or: Why Does My Diffusion Model Love Slop?","created":"2026-05-28","cited_by_count":1,"area":"diffusion"},{"id":"2605.24173","title":"Extracting Training Data from Diffusion Language Models via Infilling","created":"2026-05-22","cited_by_count":0,"area":"diffusion"},{"id":"2607.16207","title":"JUMP: Single-Pass Membership Inference on Fine-Tuned Diffusion Language Models","created":"2026-05-09","cited_by_count":0,"area":"diffusion"},{"id":"2609.33210","title":"Background Gradients Shape Memorization in Flow Matching","created":"2026-09-27","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}