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Paper Citation Record · LEDGER

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows

As of 9 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 1 inbound Pith citation observation for arXiv:2506.07534.

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

pith.paper-citation-record.v1
2506.07534 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:41:34.373921Z

measured 15 of 15 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:24:58.416482Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T18:16:11.560912Z

Reference resolution

14 of 14 outbound references displayed

  • verified exact2
  • verified fuzzy3
  • unresolved7
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 294e27cb-bca4-49b9-b8d3-d2952c1ed974 · outbound

This paper cites Wasserstein Flow Matching: Generative modeling over families of distributions.

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows Wasserstein Flow Matching: Generative modeling over families of distributions

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:41:34.431494Z

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=2026-08-07T05:41:34.347946Z digest=sha256:3c206188bfabad6fef69d31e4ad3dd30e4a0b8953a0a5d298920ff59a970b51c

Observation d21dea98-af30-4dc9-a3fb-afde0c8bc3a6 · outbound

This paper cites we sample one augmentation among color jittering, cropping, cutout, scaling and a rotation for MNIST, and also add flipping for Fashion MNIST).

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows we sample one augmentation among color jittering, cropping, cutout, scaling and a rotation for MNIST, and also add flipping for Fashion MNIST)

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:34.545709Z

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=2026-08-07T05:41:34.373921Z digest=sha256:1ae6e637b229802e5b9a6a88183bdabeea2b0e74bea15cb11f107d2e45fad224

Observation b0085545-c1ba-41ff-a87e-73fcf57bc587 · outbound

This paper cites Dataset Distillation.

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows Dataset Distillation

Reference 338

Resolution
unresolved
no resolver link, observed 2026-08-07T05:41:34.366123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:34.366123Z digest=sha256:a25a059433833dfddd849a4fc53fd79b06b9e7b405be880e80c89f224eed716c

Observation 341ab516-1fa3-4940-a68b-6f389f9807e3 · outbound

This paper cites A Wasserstein-type metric for generic mixture models, including location-scatter and group invariant measures.

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows A Wasserstein-type metric for generic mixture models, including location-scatter and group invariant measures

Reference 1725

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:41:34.444639Z

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=2026-08-07T05:41:34.344769Z digest=sha256:000843f26c27b5c4d0f70a6671eefcff8ee813d788122d11d8d57e67d3edd75e

Observation f2e09e59-29e2-42c3-b503-71dfeb0a7cb8 · outbound

This paper cites Accelerating Langevin Sampling with Birth-death.

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows Accelerating Langevin Sampling with Birth-death

Reference 2006

Resolution
unresolved
no resolver link, observed 2026-08-07T05:41:34.356928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:34.356928Z digest=sha256:a155e7b9e55bba3179bfcfc50b7c0882af8f85dae494a15a88b2e04f4ac9a1f8

Observation 982bb88d-7e0b-49bc-881a-85bd63043750 · outbound

This paper cites 7) Lee, J.

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows 7) Lee, J

Reference 2010

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:34.564037Z

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=2026-08-07T05:41:34.354177Z digest=sha256:2a5d71773aae968755da849a04eed23a49d78c983485806e337186c590c254fc

Observation 0253b470-2585-4c67-bf48-f9c938acd567 · outbound

This paper cites 1) Hertrich, J., Gr¨af, M., Beinert, R., and Steidl, G.

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows 1) Hertrich, J., Gr¨af, M., Beinert, R., and Steidl, G

Reference 2015

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:41:34.572584Z

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=2026-08-07T05:41:34.351331Z digest=sha256:13c92b7c767f59b2c4166aa5920942ad2818a715ea42907bc4b9ef21610b0141

Observation 389a7ac2-50c1-446a-b269-4a391acbb571 · outbound

This paper cites Wasserstein Diffusion on Multidimensional Spaces.

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows Wasserstein Diffusion on Multidimensional Spaces

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-07T05:41:34.362942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:34.362942Z digest=sha256:f5ac48f3bfebb28e4e0922c7b4ef9d6d83d174101270428b8ac9ac244cb5a0d1

Observation 86775f69-32e2-436f-9e4d-10ec69e72d98 · outbound

This paper cites Optimal Transport Tools (OTT): A JAX Toolbox for all things Wasserstein.

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows Optimal Transport Tools (OTT): A JAX Toolbox for all things Wasserstein

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-07T05:41:34.341570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:34.341570Z digest=sha256:295b7bed2e4f76638034b0ab01cae30e2cea827ec4b36e3a713ece4dcfccb90c

Observation 4c9ccfc3-8edd-4ec3-a96e-0a7694cce144 · outbound

This paper cites Wasserstein Gradient Flows for Moreau Envelopes of f-Divergences in Reproducing Kernel Hilbert Spaces.

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows Wasserstein Gradient Flows for Moreau Envelopes of f-Divergences in Reproducing Kernel Hilbert Spaces

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-07T05:41:34.359972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:34.359972Z digest=sha256:64ea9801b80ef46bd0311d0ab14a8fd8d279655e725b97b75c859fddf43d0fab

Observation b582447a-75c4-4677-9259-a906aebf4409 · outbound

This paper cites differential.

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows differential

Reference 2021

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T05:41:34.554833Z

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=2026-08-07T05:41:34.369514Z digest=sha256:463b56014f2d53f7df8ac99a368d336dc31b39f66150ea215df4b7f29d2ed3d9

Observation 60aabb42-e811-4389-bc2c-a87597f6d5b3 · outbound

This paper cites The Gene Mover's Distance: Single-cell similarity via Optimal Transport.

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows The Gene Mover's Distance: Single-cell similarity via Optimal Transport

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-07T05:41:34.331534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:34.331534Z digest=sha256:35c823245f9703b392ac662b2e88136e6e41b584b0de4ad198d38ad4b7d01f26

Observation 98ee1ca6-0939-4692-bf25-e30f5f8ec4a6 · outbound

This paper cites 1) Chen, Y ., Georgiou, T.

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows 1) Chen, Y ., Georgiou, T

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T05:41:34.338440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:34.338440Z digest=sha256:ed140bc05760dbca2e2d69b1498f37b2f0650f7c9771b01d3f86a34a3b8236a6

Observation 63d7ac16-7091-48a3-bfb1-07878e9c7174 · outbound

This paper cites Hierarchical Integral Probability Metrics: A distance on random probability measures with low sample complexity.

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows Hierarchical Integral Probability Metrics: A distance on random probability measures with low sample complexity

Reference 2025

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T05:41:34.528527Z

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=2026-08-07T05:41:34.335228Z digest=sha256:6688279b31cdc64893506660771a176827327d6f9dbc99fabc419d0ced5c351e

Pith citing papers

Observation bdfd761c-f56a-4045-b9f2-74b46a8cb800 · inbound

Totally convex functions, $L^2$-Optimal transport for laws of random measures, and solution to the Monge problem cites this paper.

Totally convex functions, $L^2$-Optimal transport for laws of random measures, and solution to the Monge problem Flowing Datasets with Wasserstein over Wasserstein Gradient Flows

Reference 299

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T12:24:59.032088Z

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=2026-08-05T12:24:58.416482Z digest=sha256:041fdc77b38dc6bd019efc44387bbe1ca23e45379a4af8befc4f99ae61018903