Paper Citation Record · LEDGER

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching

As of 5 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2605.00941.

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

pith.paper-citation-record.v1
2605.00941 v4

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-01T08:13:04.323547Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

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verified fuzzy16
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6151a10a-8f29-4862-ab46-a12c58e8ea5d · outbound

This paper cites Stochastic Interpolants: A Unifying Framework for Flows and Diffusions.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Stochastic Interpolants: A Unifying Framework for Flows and Diffusions

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-07-01T08:15:31.427611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 53b06f14-476c-41fc-9a88-123a5e4b4b0d · outbound

This paper cites Tweedie Moment Projected Diffusions For Inverse Problems.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Tweedie Moment Projected Diffusions For Inverse Problems

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-01T08:15:31.412021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3a970254-381d-4c8c-a2f1-1b9c5a4261c5 · outbound

This paper cites Training-Free Refinement of Flow Matching with Divergence-based Sampling.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Training-Free Refinement of Flow Matching with Divergence-based Sampling

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-07-01T08:15:31.416360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8fc4ca7a-27e1-4676-b607-cc63460218da · outbound

This paper cites Learning Patient-Specific Disease Dynamics with Latent Flow Matching for Longitudinal Imaging Generation.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Learning Patient-Specific Disease Dynamics with Latent Flow Matching for Longitudinal Imaging Generation

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-07-01T08:15:31.420742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 467a7a37-b36c-4513-9ac5-f8674acfbb80 · outbound

This paper cites Tweedie’s formula and selection bias.Journal of the American Statistical Association, 106(496):1602–1614.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Tweedie’s formula and selection bias.Journal of the American Statistical Association, 106(496):1602–1614

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.103389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8420d62b-d0dc-4329-8614-4c77351bd1cc · outbound

This paper cites Scaling rectified flow transformers for high-resolution image synthesis.Interna- tional Conference on Machine Learning.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Scaling rectified flow transformers for high-resolution image synthesis.Interna- tional Conference on Machine Learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.105324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7fbd56b0-da2f-4678-8f78-dad61ef92d84 · outbound

This paper cites Dropout as a Bayesian approximation: Representing model uncertainty in deep learn- ing.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Dropout as a Bayesian approximation: Representing model uncertainty in deep learn- ing

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.107217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b06d7821-f05a-4578-9e16-ea99f602c387 · outbound

This paper cites Mean flows for one-step generative model- ing.Advances in Neural Information Processing Systems, 38: 75460–75482, 2025.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Mean flows for one-step generative model- ing.Advances in Neural Information Processing Systems, 38: 75460–75482, 2025

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.109072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 85592480-5d98-45fa-a5bf-a0b1cd861fdc · outbound

This paper cites Quantifying epistemic uncertainty in diffusion models.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Quantifying epistemic uncertainty in diffusion models

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-01T08:15:31.407599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dfb550f6-bb7c-4c7b-a44a-6096e0cc9790 · outbound

This paper cites Flow Matching with Uncertainty Quantification and Guidance.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Flow Matching with Uncertainty Quantification and Guidance

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-07-01T08:15:31.397203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 937943aa-929b-4369-949d-e5dc5b18b2e4 · outbound

This paper cites Denoising diffu- sion probabilistic models.Advances in Neural Information Processing Systems, 33:6840–6851.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Denoising diffu- sion probabilistic models.Advances in Neural Information Processing Systems, 33:6840–6851

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.125652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5677404f-7f1b-49d7-b86e-3c4c9cd2d1a1 · outbound

This paper cites A stochastic estimator of the trace of the influence matrix for Laplacian smoothing splines.Com- munications in Statistics—Simulation and Computation, 18 (3):1059–1076.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching A stochastic estimator of the trace of the influence matrix for Laplacian smoothing splines.Com- munications in Statistics—Simulation and Computation, 18 (3):1059–1076

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.123883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fdea7c77-eb35-40ee-9efd-00806b512ab6 · outbound

This paper cites Generative Uncertainty in Diffusion Models.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Generative Uncertainty in Diffusion Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-01T08:15:31.393254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6d125123-ab8c-4aa6-8727-52efa30b4ed7 · outbound

This paper cites BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-01T08:15:31.367948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation cb702c44-fd00-4462-83d4-55c1c88dac5a · outbound

This paper cites Learning multiple layers of features from tiny images.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Learning multiple layers of features from tiny images

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.127457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 596892f6-cb4e-4509-ac9c-a0b631de0c6d · outbound

This paper cites Simple and scalable predictive uncertainty estima- tion using deep ensembles.Advances in Neural Information Processing Systems, 30.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Simple and scalable predictive uncertainty estima- tion using deep ensembles.Advances in Neural Information Processing Systems, 30

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.129340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a5b2d5ea-4366-4252-b3e2-29ace9d61e26 · outbound

This paper cites Gradient-based learning applied to document recog- nition.Proceedings of the IEEE, 86(11):2278–2324.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Gradient-based learning applied to document recog- nition.Proceedings of the IEEE, 86(11):2278–2324

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.131229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c55a94d8-919f-4c88-8d3f-934a4be46dd5 · outbound

This paper cites Geometrical properties of solutions of the porous medium equation for large times.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Geometrical properties of solutions of the porous medium equation for large times

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.117981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 08a94e27-ca5c-4e97-8deb-438e3ca0b830 · outbound

This paper cites Flow Matching for Generative Modeling.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Flow Matching for Generative Modeling

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-07-01T08:15:31.400545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f90170ca-a8a8-4618-b9ee-0da7eae54f4f · outbound

This paper cites ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-01T08:15:31.389112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4147888f-089e-402c-8245-3e0a3e6577cf · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-07-01T08:15:31.403808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b99387de-c022-4bc1-83a7-833c34ce6b0b · outbound

This paper cites On the posterior distribu- tion in denoising: Application to uncertainty quantification.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching On the posterior distribu- tion in denoising: Application to uncertainty quantification

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.116229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5b654ece-66d4-4794-b093-1d229cfe2fec · outbound

This paper cites Movie Gen: A Cast of Media Foundation Models.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Movie Gen: A Cast of Media Foundation Models

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-07-01T08:15:31.385010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4315592a-7361-486e-acd5-0bf9124841b3 · outbound

This paper cites Free Hunch: Denoiser Covariance Estimation for Diffusion Models Without Extra Costs.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Free Hunch: Denoiser Covariance Estimation for Diffusion Models Without Extra Costs

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-01T08:15:31.372454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8641e3a6-0970-4b22-988a-e1e3d3aee748 · outbound

This paper cites An empirical Bayes approach to statistics.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching An empirical Bayes approach to statistics

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.119921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 892f1df9-fed3-4288-9d3b-9a125f110a0f · outbound

This paper cites Progressive distillation for fast sampling of diffusion models.International Conference on Learning Representations.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Progressive distillation for fast sampling of diffusion models.International Conference on Learning Representations

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.121700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0a0cfd98-73bd-460e-983b-6b47ae6b2706 · outbound

This paper cites Eigenscore: Ood detection using covariance in diffusion models.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Eigenscore: Ood detection using covariance in diffusion models

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-01T08:15:31.380956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 740fa3cd-dd7d-4c3b-b998-62f101186aa2 · outbound

This paper cites Score-based generative modeling through stochastic differential equations.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Score-based generative modeling through stochastic differential equations

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.112659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f4f2a237-7ade-4f66-85eb-ebb66cf5325c · outbound

This paper cites Consistency models.International Conference on Machine Learning.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Consistency models.International Conference on Machine Learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.110872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f040d60d-86e0-4a33-9583-d752044bdb7a · outbound

This paper cites A connection between score matching and denoising autoencoders.Neural Computation, 23(7):1661– 1674.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching A connection between score matching and denoising autoencoders.Neural Computation, 23(7):1661– 1674

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T13:22:35.114428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 31e31eed-594a-48aa-b401-b043e327eb23 · outbound

This paper cites Uncertainty-Aware Distribution-to-Distribution Flow Matching for Scientific Imaging.

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching Uncertainty-Aware Distribution-to-Distribution Flow Matching for Scientific Imaging

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-07-01T08:15:31.376648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

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