Paper Citation Record · LEDGER

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces

As of 18 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 4 inbound Pith citation observations for arXiv:2505.02508.

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

pith.paper-citation-record.v1
2505.02508 v3

Coverage vector

measured 41 of 41 reference resolution

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measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T05:56:40.340025Z

Reference resolution

41 of 41 outbound references displayed

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External citation measurements

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Outbound references

Observation fcdfc762-fa95-4a98-9e47-3421431e264e · outbound

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

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 1

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Observation 3107e4d9-94b3-4f92-b195-300d94bb8412 · outbound

This paper cites Memorization and Regularization in Generative Diffusion Models.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Memorization and Regularization in Generative Diffusion Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.464266Z

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Observation 2e421f0e-22fa-4612-9b29-e52688da688c · outbound

This paper cites Laplacian eigenmaps for dimensionality reduction and data representation.Neural Computation, 15(6):1373–1396, 2003.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Laplacian eigenmaps for dimensionality reduction and data representation.Neural Computation, 15(6):1373–1396, 2003

Reference 3

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Observation da950a82-4ab2-4f17-b856-08df1716c400 · outbound

This paper cites Cambridge University Press, 2023.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Cambridge University Press, 2023

Reference 4

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Observation e4eeecdb-e4ad-4451-82d8-b1116c621051 · outbound

This paper cites Cambridge Studies in Advanced Mathematics.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Cambridge Studies in Advanced Mathematics

Reference 5

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Observation 084012b5-3241-4319-9682-15c5ad91b792 · outbound

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

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.486299Z

Source-reported events for the cited work

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Observation e5c80be3-3c8e-46a6-bd0b-54377889e223 · outbound

This paper cites Diffusion maps.Applied and computational harmonic analysis, 21(1):5–30, 2006.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Diffusion maps.Applied and computational harmonic analysis, 21(1):5–30, 2006

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.492353Z

Source-reported events for the cited work

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Observation 5b3d162b-85eb-4d11-bc01-918b0cf5b270 · outbound

This paper cites Diffusion models beat gans on imagesynthesis.Advances in neural information processing systems, 34:8780– 8794, 2021.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Diffusion models beat gans on imagesynthesis.Advances in neural information processing systems, 34:8780– 8794, 2021

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.442057Z

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Observation c60b5194-8985-4bde-b745-e26ba110b891 · outbound

This paper cites Minimax adaptive estimation in manifold inference.Elec- tronic Journal of Statistics, 15(2):5888–5932, 2021.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Minimax adaptive estimation in manifold inference.Elec- tronic Journal of Statistics, 15(2):5888–5932, 2021

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.424229Z

Source-reported events for the cited work

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Observation 59f584d6-b061-4312-9cf9-c191598f4be5 · outbound

This paper cites Measure estimation on manifolds: an optimal transport approach.Probability Theory and Related Fields, 183(1):581–647, 2022.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Measure estimation on manifolds: an optimal transport approach.Probability Theory and Related Fields, 183(1):581–647, 2022

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.407829Z

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Observation 87464efa-55fd-4550-a523-ac5474bbe1e7 · outbound

This paper cites Testing the manifold hypothesis.Journal of the American Mathematical Society, 29(4):983–1049, 2016.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Testing the manifold hypothesis.Journal of the American Mathematical Society, 29(4):983–1049, 2016

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.389674Z

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Observation a6b14b4a-03fe-4659-85cb-8b79e457f4e4 · outbound

This paper cites Interpolating between optimal transport and mmd using sinkhorn divergences.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Interpolating between optimal transport and mmd using sinkhorn divergences

Reference 12

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Observation 91380ce6-4dd0-4e75-916d-59511222dcac · outbound

This paper cites On the rate of convergence in wasser- stein distance of the empirical measure.Probability theory and related fields, 162(3):707–738, 2015.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces On the rate of convergence in wasser- stein distance of the empirical measure.Probability theory and related fields, 162(3):707–738, 2015

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.361199Z

Source-reported events for the cited work

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Observation 7ed47577-e2bb-4f8c-b703-6c1cdff25822 · outbound

This paper cites Localized diffusion models for high dimensional distributions generation.arXiv preprint arXiv:2505.04417, 2025.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Localized diffusion models for high dimensional distributions generation.arXiv preprint arXiv:2505.04417, 2025

Reference 14

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Source-reported events for the cited work

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Observation 9251916e-c5d6-408f-a417-66673afa7463 · outbound

This paper cites Diffusion models as plug-and-play priors.Advances in Neural Information Processing Systems, 35:14715–14728, 2022.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Diffusion models as plug-and-play priors.Advances in Neural Information Processing Systems, 35:14715–14728, 2022

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.532286Z

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Observation b3179866-3ba3-4cce-aac0-0f731f6ebb02 · outbound

This paper cites Kernel density estimation on riemannian manifolds: Asymptotic results.Journal of Mathematical Imaging and Vision, 34(3):235–239, 2009.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Kernel density estimation on riemannian manifolds: Asymptotic results.Journal of Mathematical Imaging and Vision, 34(3):235–239, 2009

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.332607Z

Source-reported events for the cited work

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Observation 31c869c2-75b8-4ca1-a04a-1f5e610e60f5 · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 17

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Observation 4ccf5a91-ea08-4840-815f-4ba1d6cdf07d · outbound

This paper cites Number 38.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Number 38

Reference 18

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Source-reported events for the cited work

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Observation 066ad954-f557-456a-b4dc-4eb8f98807f9 · outbound

This paper cites An analytic theory of creativity in convolutional diffusion models.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces An analytic theory of creativity in convolutional diffusion models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.555266Z

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Observation 798580e2-b25e-498b-9a7a-f6654ddcf22e · outbound

This paper cites Permutation Recovery on Manifold Data via Spectral Seriation.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Permutation Recovery on Manifold Data via Spectral Seriation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.561221Z

Source-reported events for the cited work

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Observation a86a71c1-3acf-46eb-b488-6202cbecc792 · outbound

This paper cites Geometric structures arising from kernel density estimation on riemannian manifolds.Journal of Multivariate Analysis, 114:112–126, 2013.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Geometric structures arising from kernel density estimation on riemannian manifolds.Journal of Multivariate Analysis, 114:112–126, 2013

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.295111Z

Source-reported events for the cited work

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Observation de1e8505-efbb-4721-84b5-b0dd53247875 · outbound

This paper cites Existence, uniqueness and regularity of the projection onto differentiable manifolds.Annals of global analysis and geometry, 60(3):559–587, 2021.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Existence, uniqueness and regularity of the projection onto differentiable manifolds.Annals of global analysis and geometry, 60(3):559–587, 2021

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.571600Z

Source-reported events for the cited work

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Observation 9e399b9a-9e1e-4990-b630-59c6b529332c · outbound

This paper cites A Good Score Does not Lead to A Good Generative Model.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces A Good Score Does not Lead to A Good Generative Model

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.577104Z

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Observation c480fef2-f4b7-425d-afbb-380122a4265f · outbound

This paper cites Mathematical analysis of singularities in the diffusion model under the submanifold assumption.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Mathematical analysis of singularities in the diffusion model under the submanifold assumption

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.584001Z

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Observation e320dfce-21b5-4255-9ed0-81c5e59aab0d · outbound

This paper cites How to generate random matrices from the classical compact groups.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces How to generate random matrices from the classical compact groups

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.589890Z

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Observation 66766b72-8946-4c9b-8894-de090f3551b5 · outbound

This paper cites Minimax estimation of smooth densities in wasserstein distance.The Annals of Statistics, 50(3):1519–1540, 2022.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Minimax estimation of smooth densities in wasserstein distance.The Annals of Statistics, 50(3):1519–1540, 2022

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.266764Z

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Observation 9873df0f-6827-4f99-b1de-708db323bf9d · outbound

This paper cites Diffusion models are minimax optimal distribution estimators.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Diffusion models are minimax optimal distribution estimators

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.600197Z

Source-reported events for the cited work

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Observation bbd6e1eb-a557-4133-8e1b-66f161d50859 · outbound

This paper cites Submanifold density estimation.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Submanifold density estimation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.236954Z

Source-reported events for the cited work

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Observation e4802793-ee64-4b09-aa69-3197a18a6dab · outbound

This paper cites Kernel density estimation on riemannian manifolds.Statis- tics & Probability Letters, 73(3):297–304, 2005.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Kernel density estimation on riemannian manifolds.Statis- tics & Probability Letters, 73(3):297–304, 2005

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.219963Z

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Observation a4763f4c-62c2-4e38-8c70-5a99eacb3910 · outbound

This paper cites Score-based generative models detect manifolds.Ad- vances in Neural Information Processing Systems, 35:35852–35865, 2022.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Score-based generative models detect manifolds.Ad- vances in Neural Information Processing Systems, 35:35852–35865, 2022

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.201348Z

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Observation a1fbf57a-82df-4a57-8af6-861b8805659f · outbound

This paper cites A geometric framework for understanding memorization in generative models.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces A geometric framework for understanding memorization in generative models

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.183376Z

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Observation 33f26d5c-652b-4a28-9a3f-a6ae5e88fbfa · outbound

This paper cites Roweis and Lawrence K.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Roweis and Lawrence K

Reference 32

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Observation c6bca384-7df3-428b-8e00-29dc58b651b8 · outbound

This paper cites Closed-Form Diffusion Models.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Closed-Form Diffusion Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.632041Z

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Observation 4d98e2d2-c90f-4eba-bb3c-1944aa816a2e · outbound

This paper cites From graph to manifold laplacian: The convergence rate.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces From graph to manifold laplacian: The convergence rate

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.153709Z

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Observation e89018b9-f8d0-4c26-b6cf-e726c360e99a · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Score-Based Generative Modeling through Stochastic Differential Equations

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.643497Z

Source-reported events for the cited work

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Observation aad9ee96-8fb8-4a98-90b7-31212fa71220 · outbound

This paper cites Adaptivity of diffusion models to manifold struc- tures.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Adaptivity of diffusion models to manifold struc- tures

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.133723Z

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Observation 647ed14c-5e2b-496e-814d-47ec3a17cf0a · outbound

This paper cites Nonparametric estima- tors.Introduction to Nonparametric Estimation, pages 1–76, 2009.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Nonparametric estima- tors.Introduction to Nonparametric Estimation, pages 1–76, 2009

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.115668Z

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Observation 0d499f12-9683-49c3-855d-d7aa7bfa252f · outbound

This paper cites American Mathematical Soc., 2021.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces American Mathematical Soc., 2021

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.097744Z

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Observation a105b891-667f-4201-acf8-4e8a96b51549 · outbound

This paper cites Sharp asymptotic and finite-sample rates of convergence of empirical measures in wasserstein distance.Bernoulli, 25(4A):2620–2648, 2019.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Sharp asymptotic and finite-sample rates of convergence of empirical measures in wasserstein distance.Bernoulli, 25(4A):2620–2648, 2019

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:03:34.079666Z

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Observation 190effa9-d33b-4ca8-a356-840dd1dc0350 · outbound

This paper cites Wasserstein proximal operators describe score-based generative models and resolve memorization.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces Wasserstein proximal operators describe score-based generative models and resolve memorization

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.670455Z

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Observation b0c4286a-f286-49af-a615-fa65fc2d53f0 · outbound

This paper cites The Emergence of Reproducibility and Generalizability in Diffusion Models.

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces The Emergence of Reproducibility and Generalizability in Diffusion Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:33.675591Z

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Pith citing papers

Observation 41b2b866-5e0c-48d3-9f3c-90308dd19601 · inbound

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

On The Hidden Biases of Flow Matching Samplers Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-16T21:11:16.900721Z

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Observation f414948a-851b-496b-956a-19affffa71f5 · inbound

Understanding diffusion models requires rethinking (again) generalization cites this paper.

Understanding diffusion models requires rethinking (again) generalization Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces

Reference 38

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Observation 60dbf136-03f6-442f-a510-446b19fc40fd · 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 Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-20T20:53:43.735520Z

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Observation f1acbdbd-27bd-4a6c-8521-ec43ddf3787b · inbound

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

A Quantitative Approximation Framework for Flow Distillation in Diffusion Models Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:40.341982Z

Source-reported events for the cited work

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