Paper Citation Record · LEDGER

A Computational Framework for Solving Wasserstein Lagrangian Flows

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2310.10649.

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

pith.paper-citation-record.v1
2310.10649 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:40:58.184550Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T22:23:48.215700Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 823245e7-073f-4793-846e-072164e64d1d · inbound

Machine-Learned Sampling of Conditioned Path Measures cites this paper.

Machine-Learned Sampling of Conditioned Path Measures A Computational Framework for Solving Wasserstein Lagrangian Flows

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:58.184550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 224f3d13-d0b8-4991-9f14-92c19d475995 · inbound

Generative Modeling with Flux Matching cites this paper.

Generative Modeling with Flux Matching A Computational Framework for Solving Wasserstein Lagrangian Flows

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-11T01:45:52.166687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ba5bbfbe-0ca9-40cc-b701-f0f4c039c8e4 · inbound

A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots cites this paper.

A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots A Computational Framework for Solving Wasserstein Lagrangian Flows

Reference 159

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:06:26.856069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 239eabde-51b0-4ceb-96bb-0220a95193e8 · inbound

A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots cites this paper.

A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots A Computational Framework for Solving Wasserstein Lagrangian Flows

Reference 159

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:52:59.169432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5e128c48-4718-4769-aaf0-d48a99b4704f · inbound

A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots cites this paper.

A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots A Computational Framework for Solving Wasserstein Lagrangian Flows

Reference 159

Resolution: verified exact; arxiv_id, observed 2026-05-20T22:23:48.218777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.