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Paper Citation Record · LEDGER

How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2410.23594.

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

pith.paper-citation-record.v1
2410.23594 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

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 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T03:31:36.856353Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T22:57:26.202515Z

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 dfdd75d7-8656-411c-8391-e7dd46d6eed3 · inbound

From Navigation to Refinement: Revealing the Two-Stage Nature of Flow-based Diffusion Models through Oracle Velocity cites this paper.

From Navigation to Refinement: Revealing the Two-Stage Nature of Flow-based Diffusion Models through Oracle Velocity How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-17T02:28:53.340925Z

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=2026-05-17T02:26:03.356487Z digest=sha256:26c3d243853f0b06355c8882e4ec1dbdad8459921a930471d610fa38153617d5

Observation 8c8f6f37-d3a0-4595-8566-62a93818dec0 · inbound

On The Hidden Biases of Flow Matching Samplers cites this paper.

On The Hidden Biases of Flow Matching Samplers How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 16

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T21:11:16.961617Z

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=2026-05-16T21:10:19.571440Z digest=sha256:a4536a6692bb2df36adb49951db92d74efeafddeb2cb2f29da30832a3a072620

Observation 1e63b3ea-6b9a-4e81-8836-24e32ade9767 · inbound

A Kinetic Energy Perspective of Flow Matching cites this paper.

A Kinetic Energy Perspective of Flow Matching How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-03T03:31:36.856353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T03:31:36.856353Z digest=sha256:e91e7d90712c9db1c6c86bf348a5884b083301e1871a12f6ed5011567cf7c5b7

Observation fb3c81ab-b41a-4494-8584-023ee571de97 · inbound

Momentum Guidance: Plug-and-Play Guidance for Flow Models cites this paper.

Momentum Guidance: Plug-and-Play Guidance for Flow Models How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-02T21:26:58.817847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:26:58.817847Z digest=sha256:6049fb68c1f09b8328164f21fe49484febb0299d32c62063a65413ca426d6497

Observation a1830376-886b-4c27-b137-3f7a53b8347e · inbound

Diffusion Models Memorize in Training -- and Generalize in Inference cites this paper.

Diffusion Models Memorize in Training -- and Generalize in Inference How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-21T10:54:07.980923Z

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=2026-05-21T10:52:31.849094Z digest=sha256:da94f2547adb806c1f0e1c074767650fd71d4c30fef34c42d6efa3dc88197075

Observation 468dd830-a8b6-4405-92d2-cd270c17c874 · inbound

The Amazing Stability of Flow Matching cites this paper.

The Amazing Stability of Flow Matching How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 10

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T08:37:53.885482Z

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=2026-05-10T08:37:37.238541Z digest=sha256:92e97871b9bd7a4dd9cf7b5d178a4cddc400e19e49d0c6cad18e687b44661c06

Observation e91e5613-3742-42a8-9ebf-8cd5b9b7dc14 · inbound

Exploring and Exploiting Stability in Latent Flow Matching cites this paper.

Exploring and Exploiting Stability in Latent Flow Matching How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:01:30.579202Z

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=2026-05-12T01:23:17.812123Z digest=sha256:1189797af4b27c5f9196fb5f1a77293afdba2dfc84c99082cd002f11ac66cf0a

Observation ec22853b-17b5-4668-a8f1-df7b43606a89 · inbound

Exploring and Exploiting Stability in Latent Flow Matching cites this paper.

Exploring and Exploiting Stability in Latent Flow Matching How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-07-01T13:35:46.322892Z

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=2026-06-30T22:53:43.702679Z digest=sha256:6cdfca586e43a4b23c685ea2e9bfa5c5978f291fbed1217cd6db8740abfd2425

Observation 60f9991e-05b9-444f-b816-b8d4caf68941 · inbound

Follow the Mean: Reference-Guided Flow Matching cites this paper.

Follow the Mean: Reference-Guided Flow Matching How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T06:36:26.035352Z

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=2026-05-12T04:08:34.813884Z digest=sha256:aa6ad900a60443fff54cc98a2d016fdb5765516796fe1918183752334e7940ec

Observation b8cd3b2f-2740-4449-976e-3e35bf768af2 · inbound

Follow the Mean: Reference-Guided Flow Matching cites this paper.

Follow the Mean: Reference-Guided Flow Matching How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T06:17:22.945923Z

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=2026-05-13T06:15:03.259674Z digest=sha256:aaab022902b66e7f13430ed80daa638b54a5c1961c1c9464e57a639b564c081a

Observation 01f493a1-3313-4567-bb8c-a33d4ebbf802 · inbound

Follow the Mean: Reference-Guided Flow Matching cites this paper.

Follow the Mean: Reference-Guided Flow Matching How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T14:15:46.855609Z

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=2026-06-30T22:10:36.124613Z digest=sha256:06850b82d94f32845b10d58dc92658c82357bb787c80b6c20cfd6be0e44bdac1

Observation 15d28254-7dc3-4ce6-87d1-c7bc180a1119 · inbound

Provably Learning Diffusion Models under the Manifold Hypothesis: Collapse and Refine cites this paper.

Provably Learning Diffusion Models under the Manifold Hypothesis: Collapse and Refine How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 20

Resolution
metadata mismatch
arxiv_id, observed 2026-05-21T07:39:49.410626Z

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=2026-05-21T07:36:09.475575Z digest=sha256:97f0c1e96c2ccc176eb3a22d595ca94ce479221e3bd9f9ad503ed63838092f27

Observation bab32fb3-a00c-48a1-a76a-4602e227ed03 · inbound

A Quantitative Approximation Framework for Flow Distillation in Diffusion Models cites this paper.

A Quantitative Approximation Framework for Flow Distillation in Diffusion Models How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T05:56:40.331783Z

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=2026-06-28T07:58:54.695102Z digest=sha256:9de456c2c557c09f62af29022d2e949b7e26cdd9913a4a13960a88f221f0b71c

Observation bf3dd4ce-d78b-4d62-a015-d1fade6640b3 · inbound

Where Rectified Flows Leak: Characterising Membership Signals Along the Interpolation Path cites this paper.

Where Rectified Flows Leak: Characterising Membership Signals Along the Interpolation Path How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 57

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T16:27:08.950615Z

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=arxiv_source observed=2026-06-27T22:45:28.530332Z digest=sha256:d92c0d7e3cf6cbdb463641088702f1b2839ed3aaba13329d7a7b7d1f541ce41a

Observation c143f601-3656-44df-be1f-6cab117806da · inbound

A Theoretical Analysis of Memory and Overfitting Phenomena in Stochastic Interpolation Models cites this paper.

A Theoretical Analysis of Memory and Overfitting Phenomena in Stochastic Interpolation Models How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

Reference 5

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T22:57:26.203845Z

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=arxiv_source observed=2026-06-27T18:35:15.196183Z digest=sha256:976d3c37aedb93ac9c0e3a761b5f0852b6cb69f903f85b447a9a630c6e4b0634