{"total":21,"rows":[{"id":"2503.07392","title":"SPEED: Scalable, Precise, and Efficient Concept Erasure for Diffusion Models","created":"2025-03-10","cited_by_count":36,"area":"diffusion"},{"id":"2505.17013","title":"When Are Concepts Erased From Diffusion Models?","created":"2025-05-22","cited_by_count":16,"area":"diffusion"},{"id":"2510.03302","title":"Revoking Amnesia: RL-based Trajectory Optimization to Resurrect Erased Concepts in Diffusion Models","created":"2025-09-30","cited_by_count":11,"area":"diffusion"},{"id":"2504.11850","title":"ACE: Attentional Concept Erasure in Diffusion Models","created":"2025-04-16","cited_by_count":3,"area":"diffusion"},{"id":"2602.19631","title":"Localized Concept Erasure in Text-to-Image Diffusion Models via High-Level Representation Misdirection","created":"2026-02-23","cited_by_count":3,"area":"diffusion"},{"id":"2607.23492","title":"To Erase, or Not to Erase: Robust Training-Free Concept Erasure with Preservation aware Adaptive Ranked Subspace Expansion","created":"2026-07-26","cited_by_count":3,"area":"diffusion"},{"id":"2502.17537","title":"Rethinking the Vulnerability of Concept Erasure and a New Method","created":"2025-02-24","cited_by_count":2,"area":"diffusion"},{"id":"2504.10853","title":"PT-Mark: Invisible Watermarking for Text-to-image Diffusion Models via Semantic-aware Pivotal Tuning","created":"2025-04-15","cited_by_count":2,"area":"diffusion"},{"id":"2605.28902","title":"Orthogonal Concept Erasure for Diffusion Models","created":"2026-05-27","cited_by_count":2,"area":"diffusion"},{"id":"2606.00140","title":"GEM: Geometric Erasure by Contrastive Velocity Matching in Rectified Flows","created":"2026-05-29","cited_by_count":2,"area":"diffusion"},{"id":"2605.10180","title":"What Concepts Lie Within? Detecting and Suppressing Risky Content in Diffusion Transformers","created":"2026-05-11","cited_by_count":1,"area":"diffusion"},{"id":"2608.10985","title":"PEAK: Precise and Persistent Concept Erasure via k-Sparse Autoencoders","created":"2026-08-11","cited_by_count":1,"area":"diffusion"},{"id":"2608.12829","title":"Semantic Steering for Controllable Generation: Tuning-Free Concept Erasure in Multimodal Diffusion Transformers","created":"2026-08-13","cited_by_count":1,"area":"diffusion"},{"id":"2603.00992","title":"Compensation-free Machine Unlearning in Text-to-Image Diffusion Models by Eliminating the Mutual Information","created":"2026-03-01","cited_by_count":0,"area":"diffusion"},{"id":"2605.25765","title":"Concept Unlearning via Cross-Attention Activation Projection for Diffusion Models","created":"2026-05-25","cited_by_count":0,"area":"diffusion"},{"id":"2606.01658","title":"CoreUnlearn: Rethinking Concept Unlearning through Disentangled Component-Level Erasure in Text-guided Diffusion Models","created":"2026-06-01","cited_by_count":0,"area":"diffusion"},{"id":"2606.29801","title":"Concept Removal Guidance: Evidence-Calibrated Negative Guidance for Safe Diffusion Sampling","created":"2026-06-29","cited_by_count":0,"area":"diffusion"},{"id":"2608.12806","title":"Erase but Preserve: Controllable Removal of Copyrighted Animation Characters via Optimized Semantic Anchors","created":"2026-08-13","cited_by_count":0,"area":"diffusion"},{"id":"2609.12163","title":"Certifying Concept Unlearning in Text-to-Image Diffusion Models","created":"2026-09-10","cited_by_count":0,"area":"diffusion"},{"id":"2609.35269","title":"eval-unlearn: Benchmarking unlearning in Text-to-Image Diffusion Models","created":"2026-09-28","cited_by_count":0,"area":"diffusion"},{"id":"2610.07337","title":"Compositional Concept Erasure in Text-to-Image Diffusion Models via Hierarchically Grounded Semantic Surgery","created":"2026-10-05","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}