{"total":51,"rows":[{"id":"2303.07345","title":"Erasing Concepts from Diffusion Models","created":"2023-03-13","cited_by_count":539,"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":"2401.05779","title":"Erasing Undesirable Influence in Diffusion Models","created":"2024-01-11","cited_by_count":57,"area":"diffusion"},{"id":"2402.11846","title":"UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models","created":"2024-02-19","cited_by_count":50,"area":"diffusion"},{"id":"2311.00500","title":"Intriguing Properties of Data Attribution on Diffusion Models","created":"2023-11-01","cited_by_count":47,"area":"diffusion"},{"id":"2407.15861","title":"Adversarial Attacks and Defenses on Text-to-Image Diffusion Models: A Survey","created":"2024-07-10","cited_by_count":35,"area":"diffusion"},{"id":"2408.03400","title":"Attacks and Defenses for Generative Diffusion Models: A Comprehensive Survey","created":"2024-08-06","cited_by_count":32,"area":"diffusion"},{"id":"2409.11219","title":"Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models","created":"2024-09-17","cited_by_count":23,"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":"2410.18639","title":"Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models","created":"2024-10-24","cited_by_count":22,"area":"diffusion"},{"id":"2504.09039","title":"Sculpting Memory: Multi-Concept Forgetting in Diffusion Models via Dynamic Mask and Concept-Aware Optimization","created":"2025-04-12","cited_by_count":19,"area":"diffusion"},{"id":"2503.01034","title":"Data Unlearning in Diffusion Models","created":"2025-03-02","cited_by_count":18,"area":"diffusion"},{"id":"2308.01937","title":"Training Data Protection with Compositional Diffusion Models","created":"2023-08-02","cited_by_count":17,"area":"diffusion"},{"id":"2505.17550","title":"T2VUnlearning: A Concept Erasing Method for Text-to-Video Diffusion Models","created":"2025-05-23","cited_by_count":16,"area":"diffusion"},{"id":"2410.08074","title":"Unstable Unlearning: The Hidden Risk of Concept Resurgence in Diffusion Models","created":"2024-10-10","cited_by_count":15,"area":"diffusion"},{"id":"2412.07808","title":"Boosting Alignment for Post-Unlearning Text-to-Image Generative Models","created":"2024-12-09","cited_by_count":15,"area":"diffusion"},{"id":"2409.05668","title":"Unlearning or Concealment? A Critical Analysis and Evaluation Metrics for Unlearning in Diffusion Models","created":"2024-09-09","cited_by_count":13,"area":"diffusion"},{"id":"2508.15124","title":"Side Effects of Erasing Concepts from Diffusion Models","created":"2025-08-20","cited_by_count":13,"area":"diffusion"},{"id":"2408.01014","title":"Growth Inhibitors for Suppressing Inappropriate Image Concepts in Diffusion Models","created":"2024-08-02","cited_by_count":12,"area":"diffusion"},{"id":"2403.12052","title":"A Dataset and Benchmark for Copyright Infringement Unlearning from Text-to-Image Diffusion Models","created":"2024-01-04","cited_by_count":11,"area":"diffusion"},{"id":"2408.00001","title":"Replication in Visual Diffusion Models: A Survey and Outlook","created":"2024-07-07","cited_by_count":11,"area":"diffusion"},{"id":"2602.20880","title":"When Safety Collides: Resolving Multi-Category Harmful Conflicts in Text-to-Image Diffusion via Adaptive Safety Guidance","created":"2026-02-24","cited_by_count":11,"area":"diffusion"},{"id":"2412.00782","title":"Memories of Forgotten Concepts","created":"2024-12-01","cited_by_count":10,"area":"diffusion"},{"id":"2601.06162","title":"Forget Many, Forget Right: Scalable and Precise Concept Unlearning in Diffusion Models","created":"2026-01-06","cited_by_count":9,"area":"diffusion"},{"id":"2407.14209","title":"Unlearning Concepts from Text-to-Video Diffusion Models","created":"2024-07-19","cited_by_count":8,"area":"diffusion"},{"id":"2411.02068","title":"Model Integrity when Unlearning with T2I Diffusion Models","created":"2024-11-04","cited_by_count":7,"area":"diffusion"},{"id":"2509.13007","title":"ReTrack: Data Unlearning in Diffusion Models through Redirecting the Denoising Trajectory","created":"2025-09-16","cited_by_count":5,"area":"diffusion"},{"id":"2408.16634","title":"RLCP: A Reinforcement Learning-based Copyright Protection Method for Text-to-Image Diffusion Model","created":"2024-08-29","cited_by_count":4,"area":"diffusion"},{"id":"2502.15278","title":"CopyJudge: Automated Copyright Infringement Identification and Mitigation in Text-to-Image Diffusion Models","created":"2025-02-21","cited_by_count":4,"area":"diffusion"},{"id":"2601.06163","title":"Forget-It-All: Multi-Concept Machine Unlearning via Concept-Aware Neuron Masking","created":"2026-01-07","cited_by_count":4,"area":"diffusion"},{"id":"2606.24192","title":"Co-occurring Associated REtained concepts in Diffusion Unlearning","created":"2026-06-23","cited_by_count":4,"area":"diffusion"},{"id":"2504.18563","title":"Backdoor Defense in Diffusion Models via Spatial Attention Unlearning","created":"2025-04-21","cited_by_count":2,"area":"diffusion"},{"id":"2508.12148","title":"Demystifying Foreground-Background Memorization in Diffusion Models","created":"2025-08-16","cited_by_count":2,"area":"diffusion"},{"id":"2509.21167","title":"A Unified Framework for Diffusion Model Unlearning with f-Divergence","created":"2025-09-25","cited_by_count":2,"area":"diffusion"},{"id":"2510.17917","title":"Not Every Time and Frequency Need to Be Forgotten in Diffusion Unlearning","created":"2025-10-20","cited_by_count":2,"area":"diffusion"},{"id":"2412.01118","title":"LoyalDiffusion: A Diffusion Model Guarding Against Data Replication","created":"2024-12-02","cited_by_count":1,"area":"diffusion"},{"id":"2507.03636","title":"SecureT2I: No More Unauthorized Manipulation on AI Generated Images from Prompts","created":"2025-07-04","cited_by_count":1,"area":"diffusion"},{"id":"2509.23022","title":"Copyright Infringement Detection in Text-to-Image Diffusion Models via Differential Privacy","created":"2025-09-27","cited_by_count":1,"area":"diffusion"},{"id":"2510.04058","title":"Unlearning in Diffusion models under Data Constraints: A Variational Inference Approach","created":"2025-10-05","cited_by_count":1,"area":"diffusion"},{"id":"2511.14113","title":"Coffee: Controllable Diffusion Fine-tuning","created":"2025-11-18","cited_by_count":1,"area":"diffusion"},{"id":"2603.06640","title":"Roots Beneath the Cut: Uncovering the Risk of Concept Revival in Pruning-Based Unlearning for Diffusion Models","created":"2026-02-28","cited_by_count":1,"area":"diffusion"},{"id":"2605.22311","title":"PIU: Proximity-guided Identity Unlearning in ID-Conditioned Diffusion Models","created":"2026-05-21","cited_by_count":1,"area":"diffusion"},{"id":"2610.03980","title":"FADE: Frame-Aware Diffusion-Transformer-based Multi-Concept Erasure for Video Unlearning","created":"2026-10-02","cited_by_count":1,"area":"diffusion"},{"id":"2610.05401","title":"No Concept Escapes the Audit: Auditing-Aware Unlearning for Verifiable Concept Erasure in Diffusion Models","created":"2026-10-04","cited_by_count":1,"area":"diffusion"},{"id":"2610.05601","title":"Your Unlearning Gives You Away: Identifying Erased Concepts in Diffusion Models","created":"2026-10-04","cited_by_count":1,"area":"diffusion"},{"id":"2512.01054","title":"Adaptive-lambda Subtracted Importance Sampled Scores in Machine Unlearning for DDPMs and VAEs","created":"2025-11-30","cited_by_count":0,"area":"diffusion"},{"id":"2601.22651","title":"GUDA: Counterfactual Group-wise Training Data Attribution for Diffusion Models via Unlearning","created":"2026-01-30","cited_by_count":0,"area":"diffusion"},{"id":"2603.00975","title":"Forgetting is Competition: Rethinking Unlearning as Representation Interference in Diffusion Models","created":"2026-03-01","cited_by_count":0,"area":"diffusion"},{"id":"2609.32328","title":"Continual Data Unlearning in Diffusion Models via Transition-based Regularization","created":"2026-09-26","cited_by_count":0,"area":"diffusion"},{"id":"2609.33445","title":"Concept Score Relearning: A Unified Cross-Architecture Attack on Concept Erasure","created":"2026-09-27","cited_by_count":0,"area":"diffusion"},{"id":"2609.36099","title":"Data Unlearning via Inverse Distillation","created":"2026-09-28","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}