Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:53:18.787711Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 1 inbound Pith citation observation for arXiv:2507.04619.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:53:18.787711Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-28T15:36:02.976349Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T22:16:16.280262Z
69 of 69 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation c6bea8bc-c5e5-42ea-9f9a-0d4df34b24de · outbound
Information-Guided Diffusion Sampling for Dataset Distillation Unresolved cited work
Reference 1
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Information-Guided Diffusion Sampling for Dataset Distillation Efros, and Jun-Yan Zhu
Reference 2
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Information-Guided Diffusion Sampling for Dataset Distillation Dataset distillation by matching training trajectories
Reference 3
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Information-Guided Diffusion Sampling for Dataset Distillation Generalizing dataset distillation via deep generative prior
Reference 4
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Information-Guided Diffusion Sampling for Dataset Distillation Influence-guided diffusion for dataset distillation
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Information-Guided Diffusion Sampling for Dataset Distillation Cover and Joy A
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Information-Guided Diffusion Sampling for Dataset Distillation Scaling up dataset distillation to imagenet-1k with constant memory
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Information-Guided Diffusion Sampling for Dataset Distillation Imagenet: A large-scale hierarchical image database
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Information-Guided Diffusion Sampling for Dataset Distillation Exploiting inter-sample and inter-feature relations in dataset distillation
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Information-Guided Diffusion Sampling for Dataset Distillation Diffusion models beat gans on image synthesis
Reference 10
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Information-Guided Diffusion Sampling for Dataset Distillation Calibrated Dataset Condensation for Faster Hyperparameter Search
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Observation ccef1ed3-31cb-4c06-a374-defc794894b6 · outbound
Information-Guided Diffusion Sampling for Dataset Distillation Incorporating second-order functional knowledge for better option pricing
Reference 12
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Information-Guided Diffusion Sampling for Dataset Distillation The role of entropy and reconstruction in multi-view self-supervised learning
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Information-Guided Diffusion Sampling for Dataset Distillation Efficient dataset distillation via minimax diffusion
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Information-Guided Diffusion Sampling for Dataset Distillation Efficient dataset distillation via minimax diffusion
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Information-Guided Diffusion Sampling for Dataset Distillation Towards lossless dataset distillation via difficulty-aligned trajectory matching
Reference 16
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Information-Guided Diffusion Sampling for Dataset Distillation Unresolved cited work
Reference 17
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Observation 358267ba-ad1d-408d-8372-117ee15c54fb · outbound
Information-Guided Diffusion Sampling for Dataset Distillation Flexible Diffusion Modeling of Long Videos
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Observation 2526bd6b-ac1f-45be-bdca-090098fe52f7 · outbound
Information-Guided Diffusion Sampling for Dataset Distillation Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
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Information-Guided Diffusion Sampling for Dataset Distillation Momentum contrast for unsupervised visual representation learning
Reference 20
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Observation 09f2ecf1-57c0-49ad-a6b9-974891f37fc6 · outbound
Information-Guided Diffusion Sampling for Dataset Distillation Distilling the Knowledge in a Neural Network
Reference 21
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Information-Guided Diffusion Sampling for Dataset Distillation Denoising diffusion probabilistic models
Reference 22
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Information-Guided Diffusion Sampling for Dataset Distillation Scaling Laws for Neural Language Models
Reference 23
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Observation f06b10f0-3157-4500-b7b1-a0a5a9bfc7c5 · outbound
Information-Guided Diffusion Sampling for Dataset Distillation Dataset condensation via efficient synthetic-data parameterization
Reference 24
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Information-Guided Diffusion Sampling for Dataset Distillation Dataset condensation via efficient synthetic-data parameterization
Reference 25
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Observation 878f88c1-d859-4631-8b65-dd6a71698d9b · outbound
Information-Guided Diffusion Sampling for Dataset Distillation Tiny imagenet visual recognition challenge
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Observation 33804c76-087b-4455-8eb8-e96c94d10c3d · outbound
Information-Guided Diffusion Sampling for Dataset Distillation Gradient-based learning applied to document recognition
Reference 27
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Observation 75a7274d-6feb-4a97-a56a-138939a81146 · outbound
Information-Guided Diffusion Sampling for Dataset Distillation Deep learning
Reference 28
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Observation 5d29e3d8-2e09-4a99-8bdf-a75a8d6e54b8 · outbound
Information-Guided Diffusion Sampling for Dataset Distillation Soft-label anonymous gastric x-ray image distillation
Reference 29
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Observation 52a1993e-235c-4388-a2c1-43a4af5e2d50 · outbound
Information-Guided Diffusion Sampling for Dataset Distillation Compressed gastric image generation based on soft-label dataset distillation for medical data sharing
Reference 30
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Observation 3d8afe61-55e5-4352-9f1b-2077086c27c2 · outbound
Information-Guided Diffusion Sampling for Dataset Distillation Awesome dataset distillation
Reference 31
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Information-Guided Diffusion Sampling for Dataset Distillation Dataset distillation for medical dataset sharing
Reference 32
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Information-Guided Diffusion Sampling for Dataset Distillation Importance-aware adaptive dataset distillation
Reference 33
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Information-Guided Diffusion Sampling for Dataset Distillation Generative dataset distillation: Balancing global structure and local details
Reference 34
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Reference 35
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Information-Guided Diffusion Sampling for Dataset Distillation Diversity-driven generative dataset distillation based on diffusion model with self-adaptive memory
Reference 36
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Information-Guided Diffusion Sampling for Dataset Distillation Hyperbolic dataset distillation
Reference 37
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Observation 110b41cb-4e00-40a9-9049-99b6819c051f · outbound
Information-Guided Diffusion Sampling for Dataset Distillation Dataset distillation by automatic training trajectories
Reference 38
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Information-Guided Diffusion Sampling for Dataset Distillation Elucidating the design space of classifier-guided diffusion generation
Reference 39
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Information-Guided Diffusion Sampling for Dataset Distillation Dataset meta-learning from kernel ridge-regression
Reference 40
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Reference 41
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Information-Guided Diffusion Sampling for Dataset Distillation Representation Learning with Contrastive Predictive Coding
Reference 42
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Information-Guided Diffusion Sampling for Dataset Distillation High-resolution image synthesis with latent diffusion models
Reference 43
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Reference 45
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Information-Guided Diffusion Sampling for Dataset Distillation Fleet, and Mohammad Norouzi
Reference 46
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Information-Guided Diffusion Sampling for Dataset Distillation Datadam: Efficient dataset distillation with attention matching
Reference 47
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Reference 48
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Information-Guided Diffusion Sampling for Dataset Distillation On the information bottleneck theory of deep learning
Reference 49
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Information-Guided Diffusion Sampling for Dataset Distillation Unresolved cited work
Reference 50
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Information-Guided Diffusion Sampling for Dataset Distillation D4M : Dataset distillation via disentangled diffusion model
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Information-Guided Diffusion Sampling for Dataset Distillation Generative dataset distillation based on diffusion model
Reference 52
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Information-Guided Diffusion Sampling for Dataset Distillation On the diversity and realism of distilled dataset: An efficient dataset distillation paradigm
Reference 53
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Observation 7ae5ca74-9d58-40e6-afb3-bbd3c976983f · outbound
Information-Guided Diffusion Sampling for Dataset Distillation The information bottleneck method
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Reference 55
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Information-Guided Diffusion Sampling for Dataset Distillation Dataset Distillation
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Reference 57
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Information-Guided Diffusion Sampling for Dataset Distillation Conditional mutual information constrained deep learning for classification
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Information-Guided Diffusion Sampling for Dataset Distillation An efficient dataset condensation plugin and its application to continual learning
Reference 59
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Information-Guided Diffusion Sampling for Dataset Distillation Bayes conditional distribution estimation for knowledge distillation based on conditional mutual information
Reference 61
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Information-Guided Diffusion Sampling for Dataset Distillation Squeeze, recover and relabel: Dataset condensation at imagenet scale from a new perspective
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Information-Guided Diffusion Sampling for Dataset Distillation A comprehensive survey to dataset distillation
Reference 63
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Information-Guided Diffusion Sampling for Dataset Distillation Cutmix: Regularization strategy to train strong classifiers with localizable features
Reference 64
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Reference 65
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Information-Guided Diffusion Sampling for Dataset Distillation Synthesizing informative training samples with gan
Reference 66
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Information-Guided Diffusion Sampling for Dataset Distillation Dataset condensation with gradient matching
Reference 67
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Information-Guided Diffusion Sampling for Dataset Distillation Improved distribution matching for dataset condensation
Reference 68
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Pool-Select-Refine for Allocation-Aware Generative Dataset Distillation Information-Guided Diffusion Sampling for Dataset Distillation
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