{"total":32,"rows":[{"id":"2212.08420","title":"Fake it till you make it: Learning transferable representations from synthetic ImageNet clones","created":"2022-12-16","cited_by_count":172,"area":"diffusion"},{"id":"2407.15138","title":"D$^4$M: Dataset Distillation via Disentangled Diffusion Model","created":"2024-07-21","cited_by_count":77,"area":"diffusion"},{"id":"2403.03881","title":"Unlocking Dataset Distillation with Diffusion Models","created":"2024-03-06","cited_by_count":23,"area":"diffusion"},{"id":"2506.22637","title":"CaO$_2$: Rectifying Inconsistencies in Diffusion-Based Dataset Distillation","created":"2025-06-27","cited_by_count":14,"area":"diffusion"},{"id":"2408.08610","title":"Generative Dataset Distillation Based on Diffusion Model","created":"2024-08-16","cited_by_count":13,"area":"diffusion"},{"id":"2505.19469","title":"Diversity-Driven Generative Dataset Distillation Based on Diffusion Model with Self-Adaptive Memory","created":"2025-05-26","cited_by_count":10,"area":"diffusion"},{"id":"2507.04619","title":"Information-Guided Diffusion Sampling for Dataset Distillation","created":"2025-07-07","cited_by_count":10,"area":"diffusion"},{"id":"2505.18963","title":"MGD$^3$: Mode-Guided Dataset Distillation using Diffusion Models","created":"2025-05-25","cited_by_count":7,"area":"diffusion"},{"id":"2403.07142","title":"One Category One Prompt: Dataset Distillation using Diffusion Models","created":"2024-03-11","cited_by_count":6,"area":"diffusion"},{"id":"2403.03938","title":"GUIDE: Guidance-based Incremental Learning with Diffusion Models","created":"2024-03-06","cited_by_count":5,"area":"diffusion"},{"id":"2508.01139","title":"Dataset Condensation with Color Compensation","created":"2025-08-02","cited_by_count":5,"area":"diffusion"},{"id":"2510.17421","title":"Diffusion Models as Dataset Distillation Priors","created":"2025-10-20","cited_by_count":3,"area":"diffusion"},{"id":"2604.00519","title":"Learnability-Guided Diffusion for Dataset Distillation","created":"2026-04-01","cited_by_count":3,"area":"diffusion"},{"id":"2605.03877","title":"DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models","created":"2026-05-05","cited_by_count":3,"area":"diffusion"},{"id":"2508.01264","title":"Enhancing Diffusion-based Dataset Distillation via Adversary-Guided Curriculum Sampling","created":"2025-08-02","cited_by_count":2,"area":"diffusion"},{"id":"2507.22360","title":"GVD: Guiding Video Diffusion Model for Scalable Video Distillation","created":"2025-07-30","cited_by_count":1,"area":"diffusion"},{"id":"2509.11047","title":"Data-Efficient Ensemble Weather Forecasting with Diffusion Models","created":"2025-09-14","cited_by_count":1,"area":"diffusion"},{"id":"2601.15829","title":"Towards Realistic Remote Sensing Dataset Distillation with Discriminative Prototype-guided Diffusion","created":"2026-01-22","cited_by_count":1,"area":"diffusion"},{"id":"2606.05883","title":"Geometry-Aware Dataset Condensation for Diffusion Model Training","created":"2026-06-04","cited_by_count":1,"area":"diffusion"},{"id":"2503.03110","title":"WarmFed: Federated Learning with Warm-Start for Globalization and Personalization Via Personalized Diffusion Models","created":"2025-03-05","cited_by_count":0,"area":"diffusion"},{"id":"2505.06670","title":"Video Dataset Condensation with Diffusion Models","created":"2025-05-10","cited_by_count":0,"area":"diffusion"},{"id":"2507.13074","title":"Label-Consistent Dataset Distillation with Detector-Guided Refinement","created":"2025-07-17","cited_by_count":0,"area":"diffusion"},{"id":"2509.14777","title":"Dataset Distillation for Super-Resolution without Class Labels and Pre-trained Models","created":"2025-09-18","cited_by_count":0,"area":"diffusion"},{"id":"2510.03016","title":"Learning Robust Diffusion Models from Imprecise Supervision","created":"2025-10-03","cited_by_count":0,"area":"diffusion"},{"id":"2512.03844","title":"CoDA: From Text-to-Image Diffusion Models to Training-Free Dataset Distillation","created":"2025-12-03","cited_by_count":0,"area":"diffusion"},{"id":"2602.05391","title":"Efficient Dataset Distillation for Pre-Trained Self-Supervised Models via Statistical Flow Matching","created":"2026-02-05","cited_by_count":0,"area":"diffusion"},{"id":"2602.05616","title":"Path-Guided Flow Matching for Dataset Distillation","created":"2026-02-05","cited_by_count":0,"area":"diffusion"},{"id":"2603.13960","title":"IMS3: Breaking Distributional Aggregation in Diffusion-Based Dataset Distillation","created":"2026-03-14","cited_by_count":0,"area":"diffusion"},{"id":"2603.29239","title":"Diffusion Mental Averages","created":"2026-03-31","cited_by_count":0,"area":"diffusion"},{"id":"2605.25022","title":"D3S2: Diffusion-Guided Dataset Distillation for Semantic Segmentation","created":"2026-05-24","cited_by_count":0,"area":"diffusion"},{"id":"2610.05252","title":"MGPO: Manifold-Guided Diffusion Alignment for Task-Aware Dataset Distillation","created":"2026-10-04","cited_by_count":0,"area":"diffusion"},{"id":"2610.16134","title":"ProMoDD: Dataset Distillation for 3D Human Motion via Prototype-Conditioned Diffusion Models","created":"2026-10-12","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}