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 2026-08-10T06:31:04.303077+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

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External citation measurements

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

Reference 13

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

Reference 16

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

Reference 23

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

Reference 27

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

Reference 28

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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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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

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

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

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

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

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

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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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Pith citing papers

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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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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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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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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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