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Paper Citation Record · LEDGER

Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.18705.

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

pith.paper-citation-record.v1
2403.18705 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:18:25.152152Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T04:37:31.755897Z

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 ba508f37-b21d-4d8d-a0f6-7a6e29e76f0a · inbound

Flow Matching: Markov Kernels, Stochastic Processes and Transport Plans cites this paper.

Flow Matching: Markov Kernels, Stochastic Processes and Transport Plans Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-23T04:37:31.758950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-23T04:37:05.920469Z digest=sha256:3ad267f2b57ef7f1828de00fb9d071aaaf20e1b1018c39501f8c99ddbf4e2bc4

Observation 7ba429c0-fdf1-451f-bcba-3b2c61869be8 · inbound

PnP-DA: Towards Principled Plug-and-Play Integration of Variational Data Assimilation and Generative Models cites this paper.

PnP-DA: Towards Principled Plug-and-Play Integration of Variational Data Assimilation and Generative Models Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T10:18:25.152152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:18:25.152152Z digest=sha256:468eb1e1259f470201b2109716674111dbabae7fdce56f0b532a7b3a2345facc