Paper Citation Record · LEDGER

The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2502.05673.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2502.05673 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:44:41.213231Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T19:28:52.641313Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c9bcf66e-695c-44e4-848e-8a71c762399b · inbound

Dataset Distillation via Vision-Language Category Prototype cites this paper.

Dataset Distillation via Vision-Language Category Prototype The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T21:44:41.213231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0928311c-70aa-44cf-b0c4-317bf647285b · inbound

FADRM: Fast and Accurate Data Residual Matching for Dataset Distillation cites this paper.

FADRM: Fast and Accurate Data Residual Matching for Dataset Distillation The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:56.126010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f58b1a4-a082-4628-ad55-1d862db5caa4 · inbound

Task-Specific Generative Dataset Distillation with Difficulty-Guided Sampling cites this paper.

Task-Specific Generative Dataset Distillation with Difficulty-Guided Sampling The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T20:17:25.187352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2f620f7-32c1-45b1-a5b7-9c7b8df40ee4 · inbound

Dataset Distillation as Data Compression: A Rate-Utility Perspective cites this paper.

Dataset Distillation as Data Compression: A Rate-Utility Perspective The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T15:03:29.574062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 359258a0-65df-435f-9f73-301a637cb188 · inbound

Diffusion Models as Dataset Distillation Priors cites this paper.

Diffusion Models as Dataset Distillation Priors The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-18T06:05:57.400578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3014cbab-9b0d-451c-b8e1-c43bdeafe671 · inbound

Hard Labels In! Rethinking the Role of Hard Labels in Mitigating Local Semantic Drift cites this paper.

Hard Labels In! Rethinking the Role of Hard Labels in Mitigating Local Semantic Drift The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-03T15:50:35.313915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d56dae7-4a3f-4df9-acba-b34381cc6d3e · inbound

Omnimodal Dataset Distillation via High-order Proxy Alignment cites this paper.

Omnimodal Dataset Distillation via High-order Proxy Alignment The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:05:59.661772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 88787808-a6a2-4bf6-9b86-8c15ce79c936 · inbound

SAS: Semantic-aware Sampling for Generative Dataset Distillation cites this paper.

SAS: Semantic-aware Sampling for Generative Dataset Distillation The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:23:17.017734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 556ca236-42b8-48aa-ba02-072fcf48a893 · inbound

Multimodal Distribution Matching for Vision-Language Dataset Distillation cites this paper.

Multimodal Distribution Matching for Vision-Language Dataset Distillation The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-25T04:30:19.693768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7c72db74-490d-49b4-8575-301132326acb · inbound

Geometry-Aware Dataset Condensation for Diffusion Model Training cites this paper.

Geometry-Aware Dataset Condensation for Diffusion Model Training The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 46

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T12:26:56.818575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 93880c53-c8d7-44e0-847e-db66ec901676 · inbound

Rethinking Dataset Distillation for Classification: Do Distilled Sets Outperform Coresets? cites this paper.

Rethinking Dataset Distillation for Classification: Do Distilled Sets Outperform Coresets? The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-03T19:28:52.643428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5197bc02-4067-45fc-8104-18865b9cf035 · inbound

Rank-Aware Hyperbolic Alignment for Vision-Language Dataset Distillation cites this paper.

Rank-Aware Hyperbolic Alignment for Vision-Language Dataset Distillation The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T07:24:21.244982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7c74e7a7-42dd-4ead-8a4b-6343cd2ff246 · inbound

Dataset Distillation Based on Saliency-Driven Prototype Alignment cites this paper.

Dataset Distillation Based on Saliency-Driven Prototype Alignment The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T02:50:17.234107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dadfb25-9158-417a-9a7e-38e81cd547cf · inbound

Dataset Distillation Based on Saliency-Driven Prototype Alignment cites this paper.

Dataset Distillation Based on Saliency-Driven Prototype Alignment The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T01:50:44.176823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82f263b8-e049-461c-8c2f-98405a60e0d7 · inbound

Self-Supervised Representation-Guided Generative Dataset Distillation cites this paper.

Self-Supervised Representation-Guided Generative Dataset Distillation The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T23:21:22.455243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ed145b1-48fa-4ddf-8848-3201c34f39d0 · inbound

Efficient Video Dataset Distillation via Cluster-Guided Prototype Blending cites this paper.

Efficient Video Dataset Distillation via Cluster-Guided Prototype Blending The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-05T22:10:41.717004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.