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Paper Citation Record · LEDGER

Dataset Distillation via the Wasserstein Metric

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2311.18531.

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

pith.paper-citation-record.v1
2311.18531 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:38:25.897770Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:39:36.998873Z

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 aea5dbb4-7a0d-4f15-8c3c-d3cd0c739247 · inbound

Trust-Aware Diversion for Data-Effective Distillation cites this paper.

Trust-Aware Diversion for Data-Effective Distillation Dataset Distillation via the Wasserstein Metric

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-08T20:38:25.897770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:38:25.897770Z digest=sha256:c0e16c2ace23eb979cd65d1459a03207f264ac60ff86f5e5c4f6ae557a73088f

Observation ac96e9f9-6e94-431e-9aa8-262b8d3547fc · inbound

The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions cites this paper.

The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions Dataset Distillation via the Wasserstein Metric

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-08T18:29:50.273079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:29:50.273079Z digest=sha256:c932a81cc55dc8f09849f22565e8d6bbd883266d3e45f7ef120596311b32e59e

Observation 158634ce-4b73-4f9c-b6ce-ccdb31d334f0 · inbound

Improving Noise Efficiency in Privacy-preserving Dataset Distillation cites this paper.

Improving Noise Efficiency in Privacy-preserving Dataset Distillation Dataset Distillation via the Wasserstein Metric

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T05:32:45.374982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:32:45.374982Z digest=sha256:e36c28a41baae4b555532e9c7deeca74e241095b4381e4cd028f480742b7f197

Observation 65927d45-4d30-4227-9d16-e306d6f0c9d0 · inbound

A Discrepancy-Based Perspective on Dataset Condensation cites this paper.

A Discrepancy-Based Perspective on Dataset Condensation Dataset Distillation via the Wasserstein Metric

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-04T17:57:54.799494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T17:57:54.799494Z digest=sha256:e74ba55c16c07f4ecdaed22f3a9ee74a18bff92153124282e2e2844e82222061

Observation e5d8d50a-c524-4738-bdd1-1b6cc63e7380 · inbound

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation cites this paper.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Dataset Distillation via the Wasserstein Metric

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-04T11:29:21.212959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:29:21.212959Z digest=sha256:2af8c436d44191b03ffc96f7d66e934a2cd198ef5c3d72081d8d71325be68761

Observation 020b78ee-ccc6-4dbe-abb4-768fcd78c0c3 · inbound

DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models cites this paper.

DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models Dataset Distillation via the Wasserstein Metric

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:16:29.039399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T17:42:00.634333Z digest=sha256:acd5dc0955e1a550c2e4c2b18f6270b3e415bd77a6f7b01f81ab62f5ffc35697

Observation 24c9b46c-9d4f-4a52-8e02-d57749d10064 · inbound

Distill Once, Adapt Life-Long: Exploring Dataset Distillation for Continual Test-Time Adaptation cites this paper.

Distill Once, Adapt Life-Long: Exploring Dataset Distillation for Continual Test-Time Adaptation Dataset Distillation via the Wasserstein Metric

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-07-04T03:29:29.761931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T18:03:47.140620Z digest=sha256:f83865a6b3750cc4b9294c1bc86c09bfed852182069457d1964b8e98809f75db

Observation f49863b8-e8e4-4103-a15d-2f91b488b2ad · inbound

Distill Once, Adapt Life-Long: Exploring Dataset Distillation for Continual Test-Time Adaptation cites this paper.

Distill Once, Adapt Life-Long: Exploring Dataset Distillation for Continual Test-Time Adaptation Dataset Distillation via the Wasserstein Metric

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-07-01T08:45:35.518805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-01T07:08:57.768207Z digest=sha256:8b24f6a814b0bfaa990cedd69e5f31e12ed46ecd9500b1f91e639b5eb4c3d2a3

Observation fda7fcf6-8be9-4ebc-be35-da367a07419c · inbound

Structural Assessment for Understanding and Guiding Dataset Distillation in Discrete Token Space cites this paper.

Structural Assessment for Understanding and Guiding Dataset Distillation in Discrete Token Space Dataset Distillation via the Wasserstein Metric

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-07-04T06:39:37.000220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T14:22:33.482498Z digest=sha256:445dad5ef7198db7d7eda08dd6c4c6aa57db2e9e50fba52740018598ba7220ea

Observation 551d76a2-f819-4190-84ad-605098088a1d · inbound

Condensing Large-Scale Datasets Directly with Minimal Information Loss cites this paper.

Condensing Large-Scale Datasets Directly with Minimal Information Loss Dataset Distillation via the Wasserstein Metric

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-07-02T14:07:02.395368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-02T13:59:59.488216Z digest=sha256:7e37aacbebbf0f6798788f7d6def4c8e4d3b30b70b249a2b5804a879b4ee65e4