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Paper Citation Record · LEDGER

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

As of 14 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 2026-08-14T06:32:32.682623+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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-17T02:26:03.356487Z digest=sha256:49d77fb8f8dc137925e5cc11c99722910e2b2aac3d5f4d7dd0c8743c865e1aee

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-16T21:10:19.571440Z digest=sha256:709f1e9192604c8ffde74adbd98da0193b57c84401bafe01adba0dbfabfbdce1

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=sha256:2ddd56fc2f57b0f5eb1e98e358d5ebbba10ef0c1dc78acc5d9f424d0dc823b50

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:a2d5a386966854f8911663e40e6246458aa6c6317195804d6c6d9ace79766ca6

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-21T10:52:31.849094Z digest=sha256:8f75cf8d0d6749a62c58f55b3bf0dd5e5ce19a6780a337901b724a8bb8ff3be0

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T08:37:37.238541Z digest=sha256:44dd1863125d82f595e440a0fb36d1cf394a129a8111d610cd55ff2c4578215a

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-12T01:23:17.812123Z digest=sha256:6f911dc4e04587bdaff916b17ab85106c841322f1d5a382ececb698f24250a47

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-30T22:53:43.702679Z digest=sha256:cde51c0a1785a9b4620e330962f51ed22bf6db9770c3f302dd21dc377beb6df4

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-12T04:08:34.813884Z digest=sha256:9b9c1e76799e760e4bfb45b27a281bf7f411683b4ee564b986483f371360f5c6

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-13T06:15:03.259674Z digest=sha256:3e27f6d21a07ce089ee17fca12f38364adc283b3fcd9c5ca2b8484052b878e6a

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-30T22:10:36.124613Z digest=sha256:dcdf18cef61d6e7db98612ff494ec44bbe2d579f9019a1cd332e12aa83f118f5

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-21T07:36:09.475575Z digest=sha256:259299b82a132fb21b700787de7cf65b88471ab6bb9b62a552208b8a5ef922d8

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T07:58:54.695102Z digest=sha256:43f3541552646877969e13afc48007a2703c13478e0d2b19865f5ed96625d828

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

Where Flow Matching Leaks: Characterising Membership Signals Along the Interpolation Path cites this paper.

Where Flow Matching Leaks: 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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-27T22:45:28.530332Z digest=sha256:ad0680be3eb657c791509226e9412fd33f8b56db1b55a0c9c71febbdf2baa736

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-27T18:35:15.196183Z digest=sha256:7c756a6ca0110d76a8381892d317ee95e0c7393136f5b8d9a164c669a29847c1