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Paper Citation Record · LEDGER

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models

As of 10 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 4 inbound Pith citation observations for arXiv:2501.18863.

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

pith.paper-citation-record.v1
2501.18863 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T22:27:37.543003Z

measured 49 of 49 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:49:48.434176Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T06:17:41.553379Z

Reference resolution

45 of 45 outbound references displayed

  • verified exact0
  • verified fuzzy5
  • unresolved40
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d36ebb1e-7527-40b4-9e15-8e3965308333 · outbound

This paper cites an unresolved cited work.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 1

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source=arxiv_source observed=2026-08-09T22:27:37.370629Z digest=sha256:36a7df1ba556e64e318aa04d8a78c092c95db8ad66a94268a0491d75b683df61

Observation df76071a-4f9c-46f6-95a3-a688a574a1b9 · outbound

This paper cites Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 2

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source=arxiv_source observed=2026-08-09T22:27:37.374400Z digest=sha256:275c0e171ff67e65986efd6e4724689a00fef3704f7e5f45a4ada4d8416c9b3b

Observation afee146f-9cdc-416c-a4d9-d6830af2c18a · outbound

This paper cites Nearly $d$-Linear Convergence Bounds for Diffusion Models via Stochastic Localization.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Nearly $d$-Linear Convergence Bounds for Diffusion Models via Stochastic Localization

Reference 3

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Observation d1f2ff0a-5e12-4bf8-85df-2eb5e4e6066d · outbound

This paper cites Error Bounds for Flow Matching Methods.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Error Bounds for Flow Matching Methods

Reference 4

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Observation 11925b67-97d0-484c-9591-7b7cf37a45a4 · outbound

This paper cites an unresolved cited work.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 5

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Observation ede570b2-c466-4fe8-b0f7-5aa10ea1bacc · outbound

This paper cites an unresolved cited work.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 6

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Observation bed7486e-a7fa-435b-9faf-dcd3ecf30e98 · outbound

This paper cites The probability flow ODE is provably fast.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models The probability flow ODE is provably fast

Reference 7

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Observation 533073ab-b585-47ed-b42e-a10b9e376023 · outbound

This paper cites Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions

Reference 8

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Observation ec66a262-83c1-4579-91d9-c1c94b4b117f · outbound

This paper cites Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis For DDIM-Type Samplers.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis For DDIM-Type Samplers

Reference 9

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Observation 11ece70a-1354-4dad-8673-f5e8c6aca3a2 · outbound

This paper cites T., and Shah, M.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models T., and Shah, M

Reference 10

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Observation 4259fb0e-5bdb-4ed2-9501-64688f08ebbc · outbound

This paper cites Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein Distances.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein Distances

Reference 11

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Observation 5142ccf3-d6f4-469c-94d3-8138a9dc3403 · outbound

This paper cites an unresolved cited work.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 12

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Observation 6219096f-3b19-442b-bbb2-b64271fd1e8d · outbound

This paper cites an unresolved cited work.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 13

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Observation 7f1ed008-e534-4727-926b-f3e3e0b3a487 · outbound

This paper cites G., Vignac, C., and Welling, M.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models G., Vignac, C., and Welling, M

Reference 14

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Observation 01263613-8375-4526-9f44-2305397b591b · outbound

This paper cites Convergence Analysis of Probability Flow ODE for Score-based Generative Models.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Convergence Analysis of Probability Flow ODE for Score-based Generative Models

Reference 15

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Observation 02a46191-e044-48cc-a27c-32e6bca00890 · outbound

This paper cites an unresolved cited work.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 16

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Observation f6e7346f-d367-4048-bc70-68ebe816a51b · outbound

This paper cites an unresolved cited work.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 17

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Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 18

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Observation 9f32ef23-57fa-4135-acf2-23416d981a24 · outbound

This paper cites an unresolved cited work.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 19

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Observation c057c70d-907d-4cd2-9e36-1e42d57e24b1 · outbound

This paper cites Accelerating Convergence of Score-Based Diffusion Models, Provably.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 20

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Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 21

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation be72680b-df7a-49cd-92c2-fb2d7f935ac4 · outbound

This paper cites A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Models.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Models

Reference 22

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Observation d72c6a30-025a-49e2-b73e-4ddefeaf5f0b · outbound

This paper cites and Yan, Y.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models and Yan, Y

Reference 23

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source=arxiv_source observed=2026-08-09T22:27:37.460822Z digest=sha256:5f51f7a5d10d6b56f7cf0b33d798bfbbca0909f03cd419689c289d19c6357883

Observation 35cd883e-6482-4ebb-99b6-cdee6b074ab8 · outbound

This paper cites O(d/T) Convergence Theory for Diffusion Probabilistic Models under Minimal Assumptions.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models O(d/T) Convergence Theory for Diffusion Probabilistic Models under Minimal Assumptions

Reference 24

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Observation 5b6e41c1-a1e7-43cc-a9af-4337f83d5979 · outbound

This paper cites Unified Convergence Analysis for Score-Based Diffusion Models with Deterministic Samplers.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unified Convergence Analysis for Score-Based Diffusion Models with Deterministic Samplers

Reference 25

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Observation eda53365-e90e-4ef3-86ed-ec50fc7ec6d5 · outbound

This paper cites Low-dimensional adaptation of diffusion models: Convergence in total variation.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Low-dimensional adaptation of diffusion models: Convergence in total variation

Reference 26

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Observation 725271ea-72f7-4448-8e62-63328a74bdf9 · outbound

This paper cites Diffusion Models are Minimax Optimal Distribution Estimators.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Diffusion Models are Minimax Optimal Distribution Estimators

Reference 27

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Observation aa366c37-f836-4b74-85e3-5452788e3c10 · outbound

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Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 28

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Observation 77aad06f-68bc-4c22-ae0b-dc2562108bf7 · outbound

This paper cites Linear Convergence of Diffusion Models Under the Manifold Hypothesis.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Linear Convergence of Diffusion Models Under the Manifold Hypothesis

Reference 29

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Observation 81f8ddcb-f4c2-458b-aa1b-2bddea50a6b4 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 30

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Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 31

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models L., Ghasemipour, K., Gontijo Lopes, R., Karagol Ayan, B., Salimans, T., et al

Reference 32

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Observation f5e859ea-c3d1-476d-9c94-8a4c2cfed6d4 · outbound

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Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 33

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e6631b81-fd40-425b-996d-7524ecac5402 · outbound

This paper cites Denoising Diffusion Implicit Models.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Denoising Diffusion Implicit Models

Reference 34

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Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models and Ermon, S

Reference 35

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Observation a140f21e-1ea6-49be-8134-db097f3b7469 · outbound

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Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models P., Kumar, A., Ermon, S., and Poole, B

Reference 36

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Observation a712e6de-fba2-491e-be35-1b098888ee17 · outbound

This paper cites Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation

Reference 37

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Unavailable: canonical work link unavailable.

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Observation eb20c901-4a23-4649-964a-3173dd3efa67 · outbound

This paper cites and Yang, Y.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models and Yang, Y

Reference 38

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no resolver link, observed 2026-08-09T22:27:37.516116Z

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Observation 590120d0-1b3a-4e84-ba7d-57960dceec1f · outbound

This paper cites Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial

Reference 39

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no resolver link, observed 2026-08-09T22:27:37.519915Z

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Observation 6df71f9d-d58f-4a07-b2b5-359c4035923f · outbound

This paper cites an unresolved cited work.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 40

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Observation 01c643a5-6e71-4373-873e-d0e1efcdf68d · outbound

This paper cites T., Castro, S., Kunze, J., and Erhan, D.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models T., Castro, S., Kunze, J., and Erhan, D

Reference 41

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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.

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Observation b464e434-9b44-4eb8-a649-b2b1aae7be13 · outbound

This paper cites an unresolved cited work.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 42

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Observation bdf6f6cb-822f-4f06-bdb9-5d3542fc49ee · outbound

This paper cites an unresolved cited work.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 43

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Source-reported events for the cited work

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Observation 63710a16-0c57-4a8a-9d53-625c4853144b · outbound

This paper cites Breaking the Curse of Dimensionality: Diffusion Models Efficiently Learn Low-Dimensional Distributions.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Breaking the Curse of Dimensionality: Diffusion Models Efficiently Learn Low-Dimensional Distributions

Reference 44

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Observation 15584807-3c78-49e4-b1e9-6ff2cc7b3e56 · outbound

This paper cites an unresolved cited work.

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Unresolved cited work

Reference 45

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no resolver link, observed 2026-08-09T22:27:37.543003Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T22:27:37.543003Z digest=sha256:b5265be0e7a29681fdd6528b5a36e3b4470a2da2d032ead725ed8a2ca1e773b4

Pith citing papers

Observation 21eccdb0-88ea-4959-9544-6feffc4c6e90 · inbound

Fast Convergence for High-Order ODE Solvers in Diffusion Probabilistic Models cites this paper.

Fast Convergence for High-Order ODE Solvers in Diffusion Probabilistic Models Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models

Reference 63

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no resolver link, observed 2026-08-07T00:49:48.434176Z

Source-reported events for the cited work

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Observation a03caea2-b356-4fb5-9363-30596b33917e · inbound

Faster Diffusion Models via Higher-Order Approximation cites this paper.

Faster Diffusion Models via Higher-Order Approximation Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models

Reference 47

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Source-reported events for the cited work

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Observation 09442017-030a-4687-a112-d14fcd7da792 · inbound

Intrinsic Wasserstein Rates for Score-Based Generative Models on Smooth Manifolds cites this paper.

Intrinsic Wasserstein Rates for Score-Based Generative Models on Smooth Manifolds Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models

Reference 47

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verified exact
arxiv_id, observed 2026-05-20T20:53:43.744660Z

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.

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Observation f53608d9-9ac3-4026-9b45-3e1fa9ba1b21 · inbound

Higher-order Diffusion Sampling via Chebyshev Interpolation and Gauss--Seidel Iterations cites this paper.

Higher-order Diffusion Sampling via Chebyshev Interpolation and Gauss--Seidel Iterations Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models

Reference 35

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verified exact
arxiv_id, observed 2026-07-03T06:17:41.554693Z

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.

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