Paper Citation Record · LEDGER

Convergence of Continuous Normalizing Flows for Learning Probability Distributions

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2404.00551.

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

pith.paper-citation-record.v1
2404.00551 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:56:33.499799Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation cf3bee2c-0e53-4cea-9a84-77d00e847132 · inbound

Non-asymptotic convergence bound of conditional diffusion models cites this paper.

Non-asymptotic convergence bound of conditional diffusion models Convergence of Continuous Normalizing Flows for Learning Probability Distributions

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-05T20:56:33.499799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a6a4cb7-77eb-4ad8-97c4-68c2d6cd2743 · inbound

Lipschitz regularity in Flow Matching and Diffusion Models: sharp sampling rates and functional inequalities cites this paper.

Lipschitz regularity in Flow Matching and Diffusion Models: sharp sampling rates and functional inequalities Convergence of Continuous Normalizing Flows for Learning Probability Distributions

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T20:30:47.473061Z

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 0a63b6b0-fdda-4f1f-bb25-647a6c5e5017 · inbound

RepFlow: Representation Enhanced Flow Matching for Causal Effect Estimation cites this paper.

RepFlow: Representation Enhanced Flow Matching for Causal Effect Estimation Convergence of Continuous Normalizing Flows for Learning Probability Distributions

Reference 64

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T16:41:14.855566Z

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 95fcbade-640b-4095-aa61-9c03a8792f99 · inbound

dFlowGRPO: Rate-Aware Policy Optimization for Discrete Flow Models cites this paper.

dFlowGRPO: Rate-Aware Policy Optimization for Discrete Flow Models Convergence of Continuous Normalizing Flows for Learning Probability Distributions

Reference 97

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:51:29.657464Z

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 003a3f11-9ecd-457c-b465-87af59edb463 · inbound

Ergodic Trajectory Design by Learned Pushforward Maps: Provable Coverage via Conditional Flow Matching cites this paper.

Ergodic Trajectory Design by Learned Pushforward Maps: Provable Coverage via Conditional Flow Matching Convergence of Continuous Normalizing Flows for Learning Probability Distributions

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:09:26.345755Z

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 767f599b-1f5c-4ddb-89a5-59f5c7054d21 · inbound

Panel Flow Matching: A Generative Approach to Learning Distributions of Longitudinal Data cites this paper.

Panel Flow Matching: A Generative Approach to Learning Distributions of Longitudinal Data Convergence of Continuous Normalizing Flows for Learning Probability Distributions

Reference 55

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T08:24:26.496061Z

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 41059bd0-ef53-4b3f-ad56-b39d70f01169 · inbound

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations cites this paper.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Convergence of Continuous Normalizing Flows for Learning Probability Distributions

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-01T20:13:45.161874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28585768-8f44-498c-a8d1-eff692d7b4d0 · inbound

Diffusion Bootstrap for High-Dimensional Linear Models cites this paper.

Diffusion Bootstrap for High-Dimensional Linear Models Convergence of Continuous Normalizing Flows for Learning Probability Distributions

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-31T18:14:56.787787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.