{"total":35,"rows":[{"id":"2501.18052","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","created":"2025-01-29","cited_by_count":80,"area":"diffusion"},{"id":"2410.05664","title":"Holistic Unlearning Benchmark: A Multi-Faceted Evaluation for Text-to-Image Diffusion Model Unlearning","created":"2024-10-08","cited_by_count":21,"area":"diffusion"},{"id":"2601.03305","title":"Mass Concept Erasure in Diffusion Models with Concept Hierarchy","created":"2026-01-06","cited_by_count":14,"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":"2509.21379","title":"SAEmnesia: Erasing Concepts in Diffusion Models with Supervised Sparse Autoencoders","created":"2025-09-23","cited_by_count":10,"area":"diffusion"},{"id":"2511.07970","title":"Continual Unlearning for Text-to-Image Diffusion Models: A Regularization Perspective","created":"2025-11-11","cited_by_count":10,"area":"diffusion"},{"id":"2501.15562","title":"CE-SDWV: Effective and Efficient Concept Erasure for Text-to-Image Diffusion Models via a Semantic-Driven Word Vocabulary","created":"2025-01-26","cited_by_count":8,"area":"diffusion"},{"id":"2503.09446","title":"Sparse Autoencoder as a Zero-Shot Classifier for Concept Erasing in Text-to-Image Diffusion Models","created":"2025-03-12","cited_by_count":8,"area":"diffusion"},{"id":"2501.00054","title":"AdvAnchor: Enhancing Diffusion Model Unlearning with Adversarial Anchors","created":"2024-12-28","cited_by_count":7,"area":"diffusion"},{"id":"2507.06526","title":"Concept Unlearning by Modeling Key Steps of Diffusion Process","created":"2025-07-09","cited_by_count":5,"area":"diffusion"},{"id":"2512.02657","title":"Locality-Aware Continual Unlearning for Diffusion Models","created":"2025-12-02","cited_by_count":5,"area":"diffusion"},{"id":"2410.04891","title":"Low-Rank Continual Personalization of Diffusion Models","created":"2024-10-07","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":"2511.19558","title":"SPQR: A Multi-Dimensional Benchmark for Safety Alignment under Benign Model Adaptation","created":"2025-11-24","cited_by_count":2,"area":"diffusion"},{"id":"2602.07058","title":"SPARE: Self-distillation for PARameter-Efficient Removal","created":"2026-02-04","cited_by_count":2,"area":"diffusion"},{"id":"2602.07919","title":"Selective Fine-Tuning for Targeted and Robust Concept Unlearning","created":"2026-02-08","cited_by_count":2,"area":"diffusion"},{"id":"2605.12122","title":"Disentangled Sparse Representations for Concept-Separated Diffusion Unlearning","created":"2026-05-12","cited_by_count":2,"area":"diffusion"},{"id":"2505.15450","title":"Comprehensive Evaluation and Analysis for NSFW Concept Erasure in Text-to-Image Diffusion Models","created":"2025-05-21","cited_by_count":1,"area":"diffusion"},{"id":"2507.07137","title":"Automating Evaluation of Diffusion Model Unlearning with (Vision-) Language Model World Knowledge","created":"2025-07-09","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":"2606.31699","title":"Look But Don't Touch with Sparse Autoencoders for Unlearning in Diffusion Models","created":"2026-06-30","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":"2412.18302","title":"FameBias: Embedding Manipulation Bias Attack in Text-to-Image Models","created":"2024-12-24","cited_by_count":0,"area":"diffusion"},{"id":"2502.12527","title":"Comprehensive Assessment and Analysis for NSFW Content Erasure in Text-to-Image Diffusion Models","created":"2025-02-18","cited_by_count":0,"area":"diffusion"},{"id":"2505.12395","title":"Few-Shot Concept Unlearning with Low Rank Adaptation","created":"2025-05-18","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":"2603.00133","title":"You Don't Need All That Attention: Surgical Memorization Mitigation in Text-to-Image Diffusion Models","created":"2026-02-23","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":"2605.08218","title":"Deep Dreams Are Made of This: Visualizing Monosemantic Features in Diffusion Models","created":"2026-05-06","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":"2607.06432","title":"TILDE: TILt-based Distributional Erasure for Concept Unlearning","created":"2026-07-07","cited_by_count":0,"area":"diffusion"},{"id":"2609.01433","title":"Gaussian Core LoRA: Distribution-Aware Dynamic Adaptation for Broad Concept Erasure","created":"2026-09-01","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":"2609.37537","title":"Weeding Out Bad Seeds: Initial-Noise-Robust Unlearning for Text-to-Image Diffusion Models","created":"2026-09-29","cited_by_count":0,"area":"diffusion"},{"id":"2610.14514","title":"Compositional Concepts Erasing: Disentangling Object-Style via Domain Manifold Unlearning","created":"2026-10-10","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}