{"total":94,"rows":[{"id":"2403.03206","title":"Scaling Rectified Flow Transformers for High-Resolution Image Synthesis","created":"2024-03-05","cited_by_count":4181,"area":"diffusion"},{"id":"2212.03860","title":"Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models","created":"2022-12-07","cited_by_count":424,"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":"2305.20086","title":"Understanding and Mitigating Copying in Diffusion Models","created":"2023-05-31","cited_by_count":209,"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":"2505.22705","title":"HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer","created":"2025-05-28","cited_by_count":141,"area":"diffusion"},{"id":"2310.17347","title":"CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling","created":"2023-10-26","cited_by_count":129,"area":"diffusion"},{"id":"2404.01292","title":"Measuring Style Similarity in Diffusion Models","created":"2024-04-01","cited_by_count":109,"area":"diffusion"},{"id":"2407.21720","title":"Detecting, Explaining, and Mitigating Memorization in Diffusion Models","created":"2024-07-31","cited_by_count":95,"area":"diffusion"},{"id":"2403.11052","title":"Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention","created":"2024-03-17","cited_by_count":58,"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":"2404.00922","title":"Towards Memorization-Free Diffusion Models","created":"2024-04-01","cited_by_count":50,"area":"diffusion"},{"id":"2303.12733","title":"On the De-duplication of LAION-2B","created":"2023-03-17","cited_by_count":47,"area":"diffusion"},{"id":"2411.19339","title":"Towards a Mechanistic Explanation of Diffusion Model Generalization","created":"2024-11-28","cited_by_count":42,"area":"diffusion"},{"id":"2406.02366","title":"Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models","created":"2024-06-04","cited_by_count":37,"area":"diffusion"},{"id":"2602.13344","title":"FireRed-Image-Edit-1.0 Technical Report","created":"2026-02-12","cited_by_count":36,"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":"2505.16959","title":"Bigger Isn't Always Memorizing: Early Stopping Overparameterized Diffusion Models","created":"2025-05-22","cited_by_count":25,"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":"2310.05264","title":"The Emergence of Reproducibility and Generalizability in Diffusion Models","created":"2023-10-08","cited_by_count":21,"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":"2410.21665","title":"Exploring Local Memorization in Diffusion Models via Bright Ending Attention","created":"2024-10-29","cited_by_count":19,"area":"diffusion"},{"id":"2502.05743","title":"Understanding Representation Dynamics of Diffusion Models via Low-Dimensional Modeling","created":"2025-02-09","cited_by_count":18,"area":"diffusion"},{"id":"2503.01034","title":"Data Unlearning in Diffusion Models","created":"2025-03-02","cited_by_count":18,"area":"diffusion"},{"id":"2502.02514","title":"Privacy Attacks on Image AutoRegressive Models","created":"2025-02-04","cited_by_count":15,"area":"diffusion"},{"id":"2405.21048","title":"Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling","created":"2024-05-31","cited_by_count":13,"area":"diffusion"},{"id":"2408.02226","title":"ProCreate, Don't Reproduce! Propulsive Energy Diffusion for Creative Generation","created":"2024-08-05","cited_by_count":13,"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":"2407.15328","title":"Iterative Ensemble Training with Anti-Gradient Control for Mitigating Memorization in Diffusion Models","created":"2024-07-22","cited_by_count":12,"area":"diffusion"},{"id":"2510.03813","title":"Diverse Text-to-Image Generation via Contrastive Noise Optimization","created":"2025-10-04","cited_by_count":12,"area":"diffusion"},{"id":"2403.19593","title":"Frame by Familiar Frame: Understanding Replication in Video Diffusion Models","created":"2024-03-28","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":"2310.10604","title":"Generation or Replication: Auscultating Audio Latent Diffusion Models","created":"2023-10-16","cited_by_count":10,"area":"diffusion"},{"id":"2311.02373","title":"From Trojan Horses to Castle Walls: Unveiling Bilateral Data Poisoning Effects in Diffusion Models","created":"2023-11-04","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":"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":"2405.05846","title":"An Inversion-based Measure of Memorization for Diffusion Models","created":"2024-05-09","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":"2309.07254","title":"Mitigate Replication and Copying in Diffusion Models with Generalized Caption and Dual Fusion Enhancement","created":"2023-09-13","cited_by_count":5,"area":"diffusion"},{"id":"2312.07550","title":"Understanding (Un)Intended Memorization in Text-to-Image Generative Models","created":"2023-12-06","cited_by_count":5,"area":"diffusion"},{"id":"2407.17095","title":"MemBench: Memorized Image Trigger Prompt Dataset for Diffusion Models","created":"2024-07-24","cited_by_count":5,"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":"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":"2409.19952","title":"Image Copy Detection for Diffusion Models","created":"2024-09-30","cited_by_count":4,"area":"diffusion"},{"id":"2502.07323","title":"Semantic to Structure: Learning Structural Representations for Infringement Detection","created":"2025-02-11","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":"2508.00756","title":"LeakyCLIP: Extracting Training Data from CLIP","created":"2025-08-01","cited_by_count":4,"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":"2503.00592","title":"SolidMark: Evaluating Image Memorization in Generative Models","created":"2025-03-01","cited_by_count":3,"area":"diffusion"},{"id":"2511.19811","title":"TPSO: Training-Free Diverse Image Generation via Semantic Prompt Embedding Optimization","created":"2025-11-25","cited_by_count":3,"area":"diffusion"},{"id":"2409.15650","title":"ImPoster: Text and Frequency Guidance for Subject Driven Action Personalization using Diffusion Models","created":"2024-09-24","cited_by_count":2,"area":"diffusion"},{"id":"2505.20123","title":"Understanding Generalization in Diffusion Distillation via Probability Flow Distance","created":"2025-05-26","cited_by_count":2,"area":"diffusion"},{"id":"2506.10776","title":"ME: Trigger Element Combination Backdoor Attack on Copyright Infringement","created":"2025-06-12","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":"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":"2605.06077","title":"Understanding diffusion models requires rethinking (again) generalization","created":"2026-05-07","cited_by_count":2,"area":"diffusion"},{"id":"2605.11311","title":"Couple to Control: Joint Initial Noise Design in Diffusion Models","created":"2026-05-11","cited_by_count":2,"area":"diffusion"},{"id":"2605.30825","title":"Unlearning in Diffusion Models: A Unified Framework with KL Divergence and Likelihood Constraints","created":"2026-05-29","cited_by_count":2,"area":"diffusion"},{"id":"2406.08482","title":"Words Worth a Thousand Pictures: Measuring and Understanding Perceptual Variability in Text-to-Image Generation","created":"2024-06-12","cited_by_count":1,"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":"2412.01118","title":"LoyalDiffusion: A Diffusion Model Guarding Against Data Replication","created":"2024-12-02","cited_by_count":1,"area":"diffusion"},{"id":"2501.02376","title":"Origin Identification for Text-Guided Image-to-Image Diffusion Models","created":"2025-01-04","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":"2602.00199","title":"Reducing Memorisation in Generative Models via Riemannian Bayesian Inference","created":"2026-01-30","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":"2603.10445","title":"Unlearning the Unpromptable: Prompt-free Instance Unlearning in Diffusion Models","created":"2026-03-11","cited_by_count":1,"area":"diffusion"},{"id":"2605.01221","title":"Local Hessian Spectral Filtering for Robust Intrinsic Dimension Estimation","created":"2026-05-02","cited_by_count":1,"area":"diffusion"},{"id":"2605.17938","title":"Training data attribution in diffusion models via mirrored unlearning and noise-consistent skew","created":"2026-05-18","cited_by_count":1,"area":"diffusion"},{"id":"2606.09718","title":"Evaluating the Representation Space of Diffusion Models via Self-Supervised Principles","created":"2026-06-08","cited_by_count":1,"area":"diffusion"},{"id":"2406.13933","title":"EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations","created":"2024-06-20","cited_by_count":0,"area":"diffusion"},{"id":"2407.21159","title":"Embedding Space Selection for Detecting Memorization and Fingerprinting in Generative Models","created":"2024-07-30","cited_by_count":0,"area":"diffusion"},{"id":"2411.07449","title":"Tracing the Roots: Leveraging Temporal Dynamics in Diffusion Trajectories for Origin Attribution","created":"2024-11-12","cited_by_count":0,"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":"2505.21848","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":"2511.21415","title":"DiverseVAR: Balancing Diversity and Quality of Next-Scale Visual Autoregressive Models","created":"2025-11-26","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":"2512.11194","title":"Beyond Memorization: Selective Learning for Copyright-Safe Diffusion Model Training","created":"2025-12-12","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":"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":"2605.26756","title":"Localizing Memorized Regions in Diffusion Models via Coordinate-Wise Curvature Differences","created":"2026-05-26","cited_by_count":0,"area":"diffusion"},{"id":"2607.10853","title":"Diversify Diffusion with Temperature Sampling and Variance-Corrective Time Shifting","created":"2026-07-12","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":"2608.11732","title":"Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation","created":"2026-08-12","cited_by_count":0,"area":"diffusion"},{"id":"2609.24691","title":"What Makes a Good Medical Image Tokenizer? Rethinking Reconstruction and Generation in Medical Image Tokenization","created":"2026-09-21","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":"2609.38776","title":"Distilling Diffusion Score Discrepancy for Efficient Training Data Attribution","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}