{"total":25,"rows":[{"id":"2203.11932","title":"Dataset Distillation by Matching Training Trajectories","created":"2022-03-22","cited_by_count":442,"area":null},{"id":"2301.07014","title":"Dataset Distillation: A Comprehensive Review","created":"2023-01-17","cited_by_count":127,"area":null},{"id":"2305.01649","title":"Generalizing Dataset Distillation via Deep Generative Prior","created":"2023-05-02","cited_by_count":126,"area":null},{"id":"2307.09742","title":"Improved Distribution Matching for Dataset Condensation","created":"2023-07-19","cited_by_count":124,"area":null},{"id":"2310.05773","title":"Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching","created":"2023-10-09","cited_by_count":118,"area":null},{"id":"2210.16774","title":"Dataset Distillation via Factorization","created":"2022-10-30","cited_by_count":115,"area":null},{"id":"2311.17950","title":"Generalized Large-Scale Data Condensation via Various Backbone and Statistical Matching","created":"2023-11-29","cited_by_count":69,"area":null},{"id":"2212.06152","title":"Accelerating Dataset Distillation via Model Augmentation","created":"2022-12-12","cited_by_count":62,"area":null},{"id":"2309.09455","title":"CaT: Balanced Continual Graph Learning with Graph Condensation","created":"2023-09-18","cited_by_count":52,"area":null},{"id":"2312.15927","title":"M3D: Dataset Condensation by Minimizing Maximum Mean Discrepancy","created":"2023-12-26","cited_by_count":49,"area":null},{"id":"2404.13733","title":"Elucidating the Design Space of Dataset Condensation","created":"2024-04-21","cited_by_count":40,"area":null},{"id":"2402.05011","title":"Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching","created":"2024-02-07","cited_by_count":28,"area":null},{"id":"2410.17193","title":"Emphasizing Discriminative Features for Dataset Distillation in Complex Scenarios","created":"2024-10-22","cited_by_count":18,"area":null},{"id":"2408.12483","title":"Not All Samples Should Be Utilized Equally: Towards Understanding and Improving Dataset Distillation","created":"2024-08-22","cited_by_count":14,"area":null},{"id":"2502.02854","title":"TD3: Tucker Decomposition Based Dataset Distillation Method for Sequential Recommendation","created":"2025-02-05","cited_by_count":13,"area":null},{"id":"2312.14439","title":"PUMA: Efficient Continual Graph Learning for Node Classification with Graph Condensation","created":"2023-12-22","cited_by_count":9,"area":null},{"id":"2408.14506","title":"Distilling Long-tailed Datasets","created":"2024-08-24","cited_by_count":9,"area":null},{"id":"2507.03331","title":"Task-Specific Generative Dataset Distillation with Difficulty-Guided Sampling","created":"2025-07-04","cited_by_count":8,"area":null},{"id":"2402.13007","title":"Improve Cross-Architecture Generalization on Dataset Distillation","created":"2024-02-20","cited_by_count":7,"area":null},{"id":"2408.03360","title":"Prioritize Alignment in Dataset Distillation","created":"2024-08-06","cited_by_count":4,"area":null},{"id":"2412.18926","title":"Exemplar-condensed Federated Class-incremental Learning","created":"2024-12-25","cited_by_count":2,"area":null},{"id":"2301.13389","title":"Differentially Private Kernel Inducing Points using features from ScatterNets (DP-KIP-ScatterNet) for Privacy Preserving Data Distillation","created":"2023-01-31","cited_by_count":1,"area":null},{"id":"2305.18076","title":"Towards Efficient Deep Hashing Retrieval: Condensing Your Data via Feature-Embedding Matching","created":"2023-05-29","cited_by_count":0,"area":null},{"id":"2502.12607","title":"Generalized Kernel Inducing Points by Duality Gap for Dataset Distillation","created":"2025-02-18","cited_by_count":0,"area":null},{"id":"2608.02690","title":"GLOBE: Trajectory-Aligned Gradient Matching with Structured SparseOptimization for Coreset Selection","created":"2026-08-03","cited_by_count":0,"area":null}],"next_cursor":null}