{"total":196,"rows":[{"id":"2308.14761","title":"Unified Concept Editing in Diffusion Models","created":"2023-08-25","cited_by_count":388,"area":"diffusion"},{"id":"2403.06135","title":"MACE: Mass Concept Erasure in Diffusion Models","created":"2024-03-10","cited_by_count":307,"area":"diffusion"},{"id":"2303.17591","title":"Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion Models","created":"2023-03-30","cited_by_count":301,"area":"diffusion"},{"id":"2310.10012","title":"Ring-A-Bell! How Reliable are Concept Removal Methods for Diffusion Models?","created":"2023-10-16","cited_by_count":250,"area":"diffusion"},{"id":"2310.11868","title":"To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate Unsafe Images ... For Now","created":"2023-10-18","cited_by_count":210,"area":"diffusion"},{"id":"2305.20086","title":"Understanding and Mitigating Copying in Diffusion Models","created":"2023-05-31","cited_by_count":209,"area":"diffusion"},{"id":"2311.17516","title":"MMA-Diffusion: MultiModal Attack on Diffusion Models","created":"2023-11-29","cited_by_count":194,"area":"diffusion"},{"id":"2312.16145","title":"One-Dimensional Adapter to Rule Them All: Concepts, Diffusion Models and Erasing Applications","created":"2023-12-26","cited_by_count":169,"area":"diffusion"},{"id":"2405.15234","title":"Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models","created":"2024-05-24","cited_by_count":168,"area":"diffusion"},{"id":"2311.12092","title":"Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models","created":"2023-11-20","cited_by_count":153,"area":"diffusion"},{"id":"2410.12761","title":"SAFREE: Training-Free and Adaptive Guard for Safe Text-to-Image And Video Generation","created":"2024-10-16","cited_by_count":133,"area":"diffusion"},{"id":"2308.06160","title":"DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models","created":"2023-08-11","cited_by_count":123,"area":"diffusion"},{"id":"2311.17717","title":"Receler: Reliable Concept Erasing of Text-to-Image Diffusion Models via Lightweight Erasers","created":"2023-11-29","cited_by_count":120,"area":"diffusion"},{"id":"2412.20413","title":"EraseAnything: Enabling Concept Erasure in Rectified Flow Transformers","created":"2024-12-29","cited_by_count":95,"area":"diffusion"},{"id":"2310.09336","title":"Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task","created":"2023-10-13","cited_by_count":93,"area":"diffusion"},{"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":"2309.15664","title":"Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing","created":"2023-09-27","cited_by_count":76,"area":"diffusion"},{"id":"2404.02928","title":"Jailbreaking Prompt Attack: A Controllable Adversarial Attack against Diffusion Models","created":"2024-04-02","cited_by_count":72,"area":"diffusion"},{"id":"2311.17216","title":"Self-Discovering Interpretable Diffusion Latent Directions for Responsible Text-to-Image Generation","created":"2023-11-28","cited_by_count":69,"area":"diffusion"},{"id":"2311.12832","title":"Toward effective protection against diffusion based mimicry through score distillation","created":"2023-10-02","cited_by_count":65,"area":"diffusion"},{"id":"2402.05375","title":"Get What You Want, Not What You Don't: Image Content Suppression for Text-to-Image Diffusion Models","created":"2024-02-08","cited_by_count":63,"area":"diffusion"},{"id":"2405.16341","title":"R.A.C.E.: Robust Adversarial Concept Erasure for Secure Text-to-Image Diffusion Model","created":"2024-05-25","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":"2405.19237","title":"ConceptPrune: Concept Editing in Diffusion Models via Skilled Neuron Pruning","created":"2024-05-29","cited_by_count":55,"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":"2404.00922","title":"Towards Memorization-Free Diffusion Models","created":"2024-04-01","cited_by_count":50,"area":"diffusion"},{"id":"2410.15618","title":"Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation","created":"2024-10-21","cited_by_count":50,"area":"diffusion"},{"id":"2408.16807","title":"STEREO: A Two-Stage Framework for Adversarially Robust Concept Erasing from Text-to-Image Diffusion Models","created":"2024-08-29","cited_by_count":42,"area":"diffusion"},{"id":"2307.05977","title":"Towards Safe Self-Distillation of Internet-Scale Text-to-Image Diffusion Models","created":"2023-07-12","cited_by_count":41,"area":"diffusion"},{"id":"2410.12777","title":"Meta-Unlearning on Diffusion Models: Preventing Relearning Unlearned Concepts","created":"2024-10-16","cited_by_count":40,"area":"diffusion"},{"id":"2412.06143","title":"Precise, Fast, and Low-cost Concept Erasure in Value Space: Orthogonal Complement Matters","created":"2024-12-09","cited_by_count":40,"area":"diffusion"},{"id":"2501.18950","title":"Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them","created":"2025-01-31","cited_by_count":37,"area":"diffusion"},{"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":"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":"2312.09608","title":"Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference","created":"2023-12-15","cited_by_count":34,"area":"diffusion"},{"id":"2312.12807","title":"All but One: Surgical Concept Erasing with Model Preservation in Text-to-Image Diffusion Models","created":"2023-12-20","cited_by_count":33,"area":"diffusion"},{"id":"2401.04136","title":"The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright Breaches Without Adjusting Finetuning Pipeline","created":"2024-01-07","cited_by_count":33,"area":"diffusion"},{"id":"2503.12356","title":"Localized Concept Erasure for Text-to-Image Diffusion Models Using Training-Free Gated Low-Rank Adaptation","created":"2025-03-16","cited_by_count":33,"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":"2405.07288","title":"Erasing Concepts from Text-to-Image Diffusion Models with Few-shot Unlearning","created":"2024-05-12","cited_by_count":29,"area":"diffusion"},{"id":"2402.05947","title":"Separable Multi-Concept Erasure from Diffusion Models","created":"2024-02-03","cited_by_count":28,"area":"diffusion"},{"id":"2410.14398","title":"Dynamic Negative Guidance of Diffusion Models","created":"2024-10-18","cited_by_count":28,"area":"diffusion"},{"id":"2403.06381","title":"Enhancing Semantic Fidelity in Text-to-Image Synthesis: Attention Regulation in Diffusion Models","created":"2024-03-11","cited_by_count":27,"area":"diffusion"},{"id":"2505.12677","title":"CURE: Concept Unlearning via Orthogonal Representation Editing in Diffusion Models","created":"2025-05-19","cited_by_count":27,"area":"diffusion"},{"id":"2412.07658","title":"TraSCE: Trajectory Steering for Concept Erasure","created":"2024-12-10","cited_by_count":26,"area":"diffusion"},{"id":"2503.19783","title":"Fine-Grained Erasure in Text-to-Image Diffusion-based Foundation Models","created":"2025-03-25","cited_by_count":25,"area":"diffusion"},{"id":"2310.05873","title":"Implicit Concept Removal of Diffusion Models","created":"2023-10-09","cited_by_count":23,"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":"2503.10637","title":"Distilling Diversity and Control in Diffusion Models","created":"2025-03-13","cited_by_count":22,"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":"2311.12803","title":"On Copyright Risks of Text-to-Image Diffusion Models","created":"2023-09-15","cited_by_count":20,"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":"2310.16825","title":"CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images","created":"2023-10-25","cited_by_count":16,"area":"diffusion"},{"id":"2407.07077","title":"ConceptExpress: Harnessing Diffusion Models for Single-image Unsupervised Concept Extraction","created":"2024-07-09","cited_by_count":16,"area":"diffusion"},{"id":"2412.15341","title":"Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models","created":"2024-12-19","cited_by_count":16,"area":"diffusion"},{"id":"2505.11131","title":"One Image is Worth a Thousand Words: A Usability Preservable Text-Image Collaborative Erasing Framework","created":"2025-05-16","cited_by_count":16,"area":"diffusion"},{"id":"2506.22806","title":"Concept Pinpoint Eraser for Text-to-image Diffusion Models via Residual Attention Gate","created":"2025-06-28","cited_by_count":16,"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":"2403.13807","title":"Editing Massive Concepts in Text-to-Image Diffusion Models","created":"2024-03-20","cited_by_count":15,"area":"diffusion"},{"id":"2503.07389","title":"TRCE: Towards Reliable Malicious Concept Erasure in Text-to-Image Diffusion Models","created":"2025-03-10","cited_by_count":15,"area":"diffusion"},{"id":"2404.19227","title":"Espresso: Robust Concept Filtering in Text-to-Image Models","created":"2024-04-30","cited_by_count":14,"area":"diffusion"},{"id":"2503.15197","title":"Detect-and-Guide: Self-regulation of Diffusion Models for Safe Text-to-Image Generation via Guideline Token Optimization","created":"2025-03-19","cited_by_count":13,"area":"diffusion"},{"id":"2404.13706","title":"Concept Arithmetics for Circumventing Concept Inhibition in Diffusion Models","created":"2024-04-21","cited_by_count":12,"area":"diffusion"},{"id":"2405.19708","title":"Text Guided Image Editing with Automatic Concept Locating and Forgetting","created":"2024-05-30","cited_by_count":12,"area":"diffusion"},{"id":"2406.15213","title":"Backdooring Bias ($B^2$) into Stable Diffusion Models","created":"2024-06-21","cited_by_count":12,"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":"2405.14677","title":"RectifID: Personalizing Rectified Flow with Anchored Classifier Guidance","created":"2024-05-23","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":"2412.01244","title":"Concept Replacer: Replacing Sensitive Concepts in Diffusion Models via Precision Localization","created":"2024-12-02","cited_by_count":11,"area":"diffusion"},{"id":"2412.02542","title":"Unveiling Concept Attribution in Diffusion Models","created":"2024-12-03","cited_by_count":11,"area":"diffusion"},{"id":"2502.16368","title":"Concept Corrector: Erase concepts on the fly for text-to-image diffusion models","created":"2025-02-22","cited_by_count":11,"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":"2403.19738","title":"MIST: Mitigating Intersectional Bias with Disentangled Cross-Attention Editing in Text-to-Image Diffusion Models","created":"2024-03-28","cited_by_count":10,"area":"diffusion"},{"id":"2412.00782","title":"Memories of Forgotten Concepts","created":"2024-12-01","cited_by_count":10,"area":"diffusion"},{"id":"2507.07139","title":"Image Can Bring Your Memory Back: A Novel Multi-Modal Guided Attack against Image Generation Model Unlearning","created":"2025-07-09","cited_by_count":10,"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":"2304.12536","title":"Exploring Compositional Visual Generation with Latent Classifier Guidance","created":"2023-04-25","cited_by_count":9,"area":"diffusion"},{"id":"2404.08030","title":"Rethinking Artistic Copyright Infringements in the Era of Text-to-Image Generative Models","created":"2024-04-11","cited_by_count":9,"area":"diffusion"},{"id":"2406.14855","title":"Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models","created":"2024-06-21","cited_by_count":9,"area":"diffusion"},{"id":"2502.14896","title":"A Comprehensive Survey on Concept Erasure in Text-to-Image Diffusion Models","created":"2025-02-17","cited_by_count":9,"area":"diffusion"},{"id":"2504.21072","title":"Erased but Not Forgotten: How Backdoors Compromise Concept Erasure","created":"2025-04-29","cited_by_count":9,"area":"diffusion"},{"id":"2505.16174","title":"Erased or Dormant? Rethinking Concept Erasure Through Reversibility","created":"2025-05-22","cited_by_count":9,"area":"diffusion"},{"id":"2507.16302","title":"Towards Resilient Safety-driven Unlearning for Diffusion Models against Downstream Fine-tuning","created":"2025-07-22","cited_by_count":9,"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":"2403.12326","title":"Hiding and Recovering Knowledge in Text-to-Image Diffusion Models via Learnable Prompts","created":"2024-03-18","cited_by_count":8,"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":"2509.05625","title":"SuMa: A Subspace Mapping Approach for Robust and Effective Concept Erasure in Text-to-Image Diffusion Models","created":"2025-09-06","cited_by_count":8,"area":"diffusion"},{"id":"2510.22851","title":"Semantic Surgery: Zero-Shot Concept Erasure in Diffusion Models","created":"2025-10-26","cited_by_count":8,"area":"diffusion"},{"id":"2404.12541","title":"GenVideo: One-shot Target-image and Shape Aware Video Editing using T2I Diffusion Models","created":"2024-04-18","cited_by_count":7,"area":"diffusion"},{"id":"2412.11044","title":"Understanding and Mitigating Memorization in Diffusion Models for Tabular Data","created":"2024-12-15","cited_by_count":7,"area":"diffusion"},{"id":"2503.16835","title":"Safe and Reliable Diffusion Models via Subspace Projection","created":"2025-03-21","cited_by_count":7,"area":"diffusion"},{"id":"2505.18832","title":"Localizing Knowledge in Diffusion Transformers","created":"2025-05-24","cited_by_count":7,"area":"diffusion"},{"id":"2511.10721","title":"Fast Data Attribution for Text-to-Image Models","created":"2025-11-13","cited_by_count":7,"area":"diffusion"},{"id":"2412.00580","title":"Continuous Concepts Removal in Text-to-image Diffusion Models","created":"2024-11-30","cited_by_count":6,"area":"diffusion"}],"next_cursor":"100"}