{"total":71,"rows":[{"id":"2505.17638","title":"Why Diffusion Models Don't Memorize: The Role of Implicit Dynamical Regularization in Training","created":"2025-05-23","cited_by_count":81,"area":"diffusion"},{"id":"2409.02426","title":"Breaking the Curse of Dimensionality: Diffusion Models Efficiently Learn Low-Dimensional Distributions","created":"2024-09-04","cited_by_count":53,"area":"diffusion"},{"id":"2508.17689","title":"On the Edge of Memorization in Diffusion Models","created":"2025-08-25","cited_by_count":22,"area":"diffusion"},{"id":"2411.16738","title":"Classifier-Free Guidance inside the Attraction Basin May Cause Memorization","created":"2024-11-23","cited_by_count":21,"area":"diffusion"},{"id":"2412.04140","title":"Understanding and Mitigating Memorization in Generative Models via Sharpness of Probability Landscapes","created":"2024-12-05","cited_by_count":21,"area":"diffusion"},{"id":"2510.02305","title":"Diffusion Models and the Manifold Hypothesis: Log-Domain Smoothing is Geometry Adaptive","created":"2025-10-02","cited_by_count":20,"area":"diffusion"},{"id":"2410.21665","title":"Exploring Local Memorization in Diffusion Models via Bright Ending Attention","created":"2024-10-29","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":"2509.16499","title":"A Closer Look at Model Collapse: From a Generalization-to-Memorization Perspective","created":"2025-09-20","cited_by_count":18,"area":"diffusion"},{"id":"2502.21278","title":"Does Generation Require Memorization? Creative Diffusion Models using Ambient Diffusion","created":"2025-02-28","cited_by_count":17,"area":"diffusion"},{"id":"2502.02514","title":"Privacy Attacks on Image AutoRegressive Models","created":"2025-02-04","cited_by_count":15,"area":"diffusion"},{"id":"2512.20963","title":"Generalization of Diffusion Models Arises with a Balanced Representation Space","created":"2025-12-24","cited_by_count":11,"area":"diffusion"},{"id":"2505.05787","title":"Demystifying Diffusion Policies: Action Memorization and Simple Lookup Table Alternatives","created":"2025-05-09","cited_by_count":9,"area":"diffusion"},{"id":"2602.15030","title":"Image Generation with a Sphere Encoder","created":"2026-02-16","cited_by_count":8,"area":"diffusion"},{"id":"2408.08307","title":"What Secrets Do Your Manifolds Hold? Understanding the Local Geometry of Generative Models","created":"2024-08-15","cited_by_count":7,"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":"2510.08625","title":"Adjusting Initial Noise to Mitigate Memorization in Text-to-Image Diffusion Models","created":"2025-10-08","cited_by_count":7,"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":"2412.01528","title":"CopyrightShield: Enhancing Diffusion Model Security against Copyright Infringement Attacks","created":"2024-12-02","cited_by_count":6,"area":"diffusion"},{"id":"2509.25705","title":"How Diffusion Models Memorize","created":"2025-09-30","cited_by_count":6,"area":"diffusion"},{"id":"2410.21669","title":"Investigating Memorization in Video Diffusion Models","created":"2024-10-29","cited_by_count":5,"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":"2606.14390","title":"Local Coverage Governs Memorization in Diffusion Models","created":"2026-06-12","cited_by_count":5,"area":"diffusion"},{"id":"2409.19952","title":"Image Copy Detection for Diffusion Models","created":"2024-09-30","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":"2409.07025","title":"CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion","created":"2024-09-11","cited_by_count":3,"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":"2502.07516","title":"The Devil is in the Prompts: De-Identification Traces Enhance Memorization Risks in Synthetic Chest X-Ray Generation","created":"2025-02-11","cited_by_count":3,"area":"diffusion"},{"id":"2503.00592","title":"SolidMark: Evaluating Image Memorization in Generative Models","created":"2025-03-01","cited_by_count":3,"area":"diffusion"},{"id":"2507.06547","title":"Concept-TRAK: Understanding how diffusion models learn concepts through concept-level attribution","created":"2025-07-09","cited_by_count":3,"area":"diffusion"},{"id":"2509.22723","title":"Responsible Diffusion: A Comprehensive Survey on Safety, Ethics, and Trust in Diffusion Models","created":"2025-09-25","cited_by_count":3,"area":"diffusion"},{"id":"2602.17846","title":"Two Calm Ends and the Wild Middle: A Geometric Picture of Memorization in Diffusion Models","created":"2026-02-19","cited_by_count":3,"area":"diffusion"},{"id":"2410.22149","title":"Capacity Control is an Effective Memorization Mitigation Mechanism in Text-Conditional Diffusion Models","created":"2024-10-29","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":"2509.14934","title":"Mitigating data replication in text-to-audio generative diffusion models through anti-memorization guidance","created":"2025-09-18","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":"2601.20642","title":"Detecting and Mitigating Memorization in Diffusion Models through Anisotropy of the Log-Probability","created":"2026-01-28","cited_by_count":2,"area":"diffusion"},{"id":"2603.13419","title":"Diffusion Models Memorize in Training -- and Generalize in Inference","created":"2026-03-12","cited_by_count":2,"area":"diffusion"},{"id":"2410.03039","title":"Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models","created":"2024-10-03","cited_by_count":1,"area":"diffusion"},{"id":"2410.03640","title":"Real-World Benchmarks Make Membership Inference Attacks Fail on Diffusion Models","created":"2024-10-04","cited_by_count":1,"area":"diffusion"},{"id":"2410.21088","title":"Shallow Diffuse: Robust and Invisible Watermarking through Low-Dimensional Subspaces in Diffusion Models","created":"2024-10-28","cited_by_count":1,"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":"2505.20955","title":"Enhancing Membership Inference Attacks on Diffusion Models from a Frequency-Domain Perspective","created":"2025-05-27","cited_by_count":1,"area":"diffusion"},{"id":"2505.22322","title":"A Closer Look on Memorization in Tabular Diffusion Model: A Data-Centric Perspective","created":"2025-05-28","cited_by_count":1,"area":"diffusion"},{"id":"2508.16154","title":"On the Collapse Errors Induced by the Deterministic Sampler for Diffusion Models","created":"2025-08-22","cited_by_count":1,"area":"diffusion"},{"id":"2510.22899","title":"On the Anisotropy of Score-Based Generative Models","created":"2025-10-27","cited_by_count":1,"area":"diffusion"},{"id":"2512.20666","title":"Dominant vs. Dominated: Concept-Level Generative Collapse in Diffusion Models","created":"2025-12-19","cited_by_count":1,"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":"2603.02919","title":"Interpretable Motion-Attentive Maps: Spatio-Temporally Localizing Concepts in Video Diffusion Transformers","created":"2026-03-03","cited_by_count":1,"area":"diffusion"},{"id":"2603.10445","title":"Unlearning the Unpromptable: Prompt-free Instance Unlearning in Diffusion Models","created":"2026-03-11","cited_by_count":1,"area":"diffusion"},{"id":"2502.09434","title":"Redistribute Ensemble Training for Mitigating Memorization in Diffusion Models","created":"2025-02-13","cited_by_count":0,"area":"diffusion"},{"id":"2505.08246","title":"Identifying Memorization of Diffusion Models through $p$-Laplace Analysis: Estimators, Bounds and Applications","created":"2025-05-13","cited_by_count":0,"area":"diffusion"},{"id":"2505.21848","title":"FPAN: Mitigating Replication in Diffusion Models through the Fine-Grained Probabilistic Addition of Noise to Token Embeddings","created":"2025-05-28","cited_by_count":0,"area":"diffusion"},{"id":"2511.11435","title":"The Persistence of Cultural Memory: Investigating Multimodal Iconicity in Diffusion Models","created":"2025-11-14","cited_by_count":0,"area":"diffusion"},{"id":"2512.10655","title":"CAPTAIN: Semantic Feature Injection for Memorization Mitigation in Text-to-Image Diffusion Models","created":"2025-12-11","cited_by_count":0,"area":"diffusion"},{"id":"2601.21628","title":"Noise as a Probe: Membership Inference Attacks on Diffusion Models Leveraging Initial Noise","created":"2026-01-29","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":"2604.23552","title":"On the Memorization of Consistency Distillation for Diffusion Models","created":"2026-04-26","cited_by_count":0,"area":"diffusion"},{"id":"2604.26841","title":"Language Diffusion Models are Associative Memories Capable of Retrieving Unseen Data","created":"2026-04-29","cited_by_count":0,"area":"diffusion"},{"id":"2605.02908","title":"Memorization In Stable Diffusion Is Unexpectedly Driven by CLIP Embeddings","created":"2026-04-06","cited_by_count":0,"area":"diffusion"},{"id":"2605.10439","title":"Filtering Memorization from Parameter-Space in Diffusion Models","created":"2026-05-11","cited_by_count":0,"area":"diffusion"},{"id":"2605.18253","title":"Machine Unlearning for Masked Diffusion Language Models","created":"2026-05-18","cited_by_count":0,"area":"diffusion"},{"id":"2605.26756","title":"Localizing Memorized Regions in Diffusion Models via Coordinate-Wise Curvature Differences","created":"2026-05-26","cited_by_count":0,"area":"diffusion"},{"id":"2607.18516","title":"Signed Rectified Flow: Negativity-Controlled Generation","created":"2026-07-20","cited_by_count":0,"area":"diffusion"},{"id":"2607.24296","title":"PAC-DP: PAC-Bayesian Diffusion Policy Learning","created":"2026-07-27","cited_by_count":0,"area":"diffusion"},{"id":"2608.11732","title":"Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation","created":"2026-08-12","cited_by_count":0,"area":"diffusion"},{"id":"2609.32420","title":"Carnator: Fast Text-to-Video Generation with Generation-Native Compatibility-Guided Cross-Request Reuse","created":"2026-09-26","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"},{"id":"2609.39648","title":"From Modes to Memories: Characterizing the Scale-Space Dynamics of Diffusion Models","created":"2026-09-30","cited_by_count":0,"area":"diffusion"},{"id":"2610.01723","title":"Rethinking Memorization Mitigation in Diffusion Models: Reinforcing Text Conditioning","created":"2026-10-01","cited_by_count":0,"area":"diffusion"},{"id":"2610.02780","title":"Controlling Polar Exposure to Delay Memorization in Diffusion Models","created":"2026-10-02","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}