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Paper Citation Record · LEDGER

Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 28 inbound Pith citation observations for arXiv:2409.18804.

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

pith.paper-citation-record.v1
2409.18804 v3

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 28 of 28 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T01:03:33.457126Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T12:49:52.498904Z

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 77beb34d-7ae2-4913-b5d2-42092dfd63b7 · inbound

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

Low-dimensional adaptation of diffusion models: Convergence in total variation Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 2

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no resolver link, observed 2026-08-10T16:42:26.272564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:42:26.272564Z digest=sha256:2c36365cf4a5f5b371487efb2b506823a76d325f6a3350020317a26c4e6a776f

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

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models cites this paper.

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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no resolver link, observed 2026-08-09T22:27:37.374400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T22:27:37.374400Z digest=sha256:f3e277f2d4daa09f46f38f30a44b547e8039c99de3ded6ec5a24d45a3168533b

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

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces cites this paper.

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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no resolver link, observed 2026-08-16T01:03:33.457126Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T01:03:33.457126Z digest=sha256:c3aaae4b2c651185f8b89cbde94bf2ee6eb6f783e6db0c7614ceef2d5bb12cf1

Observation ebbc430f-6932-43a3-a456-214ea9ae070c · inbound

Assessing the Quality of Denoising Diffusion Models in Wasserstein Distance: Noisy Score and Optimal Bounds cites this paper.

Assessing the Quality of Denoising Diffusion Models in Wasserstein Distance: Noisy Score and Optimal Bounds Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 2024

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no resolver link, observed 2026-08-07T04:51:16.580890Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:51:16.580890Z digest=sha256:ceea0915ec1ef29a4f82d891f1dfe24c34b2cdc8c8814e2e934b198c5c23139a

Observation 2c46298c-6d55-4a35-af66-ed7d47514f84 · 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 Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 3

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no resolver link, observed 2026-08-07T00:49:43.063830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:49:43.063830Z digest=sha256:3459ad7760f4988174235c95e626169bedfb823504a644b511a9ee9436e6bece

Observation c38d1631-e576-43eb-9573-30acae01a2f5 · inbound

Generative model for optimal density estimation on unknown manifold cites this paper.

Generative model for optimal density estimation on unknown manifold Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 2017

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no resolver link, observed 2026-08-15T18:45:44.789705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:45:44.789705Z digest=sha256:01e6b7883219420e1f904f8c50c47193d5b38d5fbdb657cdbadab6e1d6c31afa

Observation 74e011cf-8938-4d64-9676-24a83a04fca6 · inbound

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

Faster Diffusion Models via Higher-Order Approximation Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 2

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no resolver link, observed 2026-08-06T21:45:12.399236Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:45:12.399236Z digest=sha256:c6170d0660555e25f5cffeec632b5442a89980bace41930d715ead89191958bb

Observation 00cb1544-b0b2-4974-90f6-df1c0d567569 · inbound

Implicit Regularisation in Diffusion Models: An Algorithm-Dependent Generalisation Analysis cites this paper.

Implicit Regularisation in Diffusion Models: An Algorithm-Dependent Generalisation Analysis Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 4

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no resolver link, observed 2026-08-06T20:15:02.178672Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:15:02.178672Z digest=sha256:50e285f095215ae78f7dc0a10c2741c2b39eb1fca75efc47c39e7ed4af3a545c

Observation e9c142e2-377a-462e-a619-ad3e9ec5a6eb · inbound

Generalization bounds for score-based generative models: a synthetic proof cites this paper.

Generalization bounds for score-based generative models: a synthetic proof Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 1982

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:54:28.161064Z digest=sha256:19b61bb6b4967d0d8082b5a4ccdef74ced88d1812714f18d6a393d8a9abe7673

Observation 0b3283b0-8492-46ce-b9bf-8544f606a05c · inbound

Diffusion and Flow-based Copulas: Forgetting and Remembering Dependencies cites this paper.

Diffusion and Flow-based Copulas: Forgetting and Remembering Dependencies Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 3

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-21T21:51:41.885012Z digest=sha256:1560fd19d34da8584022f11bf72ff01bd2a4f1a8138927812ab1183c49a6f2d1

Observation 5ac679d9-b798-4618-b7af-24080ac65c1e · inbound

Fast Score-Based Sampling via Log-Concave Reductions cites this paper.

Fast Score-Based Sampling via Log-Concave Reductions Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 3

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no resolver link, observed 2026-08-03T13:36:13.734744Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:36:13.734744Z digest=sha256:2afad124eff587942905e6a6818253e841b7ca25967d4e1cb8b60b759540acd1

Observation 65f92eb8-dda2-453e-a1f7-a1842c682250 · inbound

Diffusion Model for Manifold Data: Score Decomposition, Curvature, and Statistical Complexity cites this paper.

Diffusion Model for Manifold Data: Score Decomposition, Curvature, and Statistical Complexity Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 1

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-15T06:41:38.834864Z digest=sha256:1058c9d04bb4432ee1e1dc02049a0c2f842fe317815ef35962e0884cdf5aec09

Observation a02f17ff-0b29-4f60-ac97-fbe71cf117b4 · inbound

Transformers Learn the Optimal DDPM Denoiser for Multi-Token GMMs cites this paper.

Transformers Learn the Optimal DDPM Denoiser for Multi-Token GMMs Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 4

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-10T16:23:50.751356Z digest=sha256:f67740c1c03c715ed6a7403c77a32db0b0d949b337cd380dbe841dab2197f963

Observation a60d9849-604d-402f-b2fc-85ffd0e40c4a · inbound

Simultaneous CNN Approximation on Manifolds with Applications to Boundary Value Problems cites this paper.

Simultaneous CNN Approximation on Manifolds with Applications to Boundary Value Problems Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 1

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-08T18:23:07.197611Z digest=sha256:b27e6aae84baf1d05ba749dddf642b553c89013c104864c153e1d1112594d716

Observation 59e69ddf-db31-443e-92f7-eb8dc03a996b · inbound

Simultaneous CNN Approximation on Manifolds with Applications to Boundary Value Problems cites this paper.

Simultaneous CNN Approximation on Manifolds with Applications to Boundary Value Problems Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 1

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-07-01T00:13:09.986377Z digest=sha256:cfe22bb344bac59e7e74aaac06284eb8b0f37d86257ed56682d5373865fddbdb

Observation 9794aee9-dbd3-424c-97de-cd12e0ea3db2 · inbound

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

Understanding diffusion models requires rethinking (again) generalization Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 3

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-08T13:53:59.565702Z digest=sha256:712cd482053645427feb224143261f1e1eadc7f9ac6854eb86f43b7e9363b249

Observation 1f452728-9513-438e-9951-079956ea0105 · inbound

Statistical Convergence of Spherical First Hitting Diffusion Models cites this paper.

Statistical Convergence of Spherical First Hitting Diffusion Models Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 3

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-11T01:52:20.620447Z digest=sha256:f87c9252203599fd84ddcdf3a9ea1cd9ef094d1db28f1f9640be2f3812ac9508

Observation b5e133c2-4fe3-43bc-96ee-c730d7907e98 · inbound

On the Limits of Latent Reuse in Diffusion Models cites this paper.

On the Limits of Latent Reuse in Diffusion Models Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 65

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-14T18:38:49.566101Z digest=sha256:30d1cba0e038a1fe491b67754aa29c2ed737dcaa4e138cb5714cae2c88ab1704

Observation 99f0057b-e034-4b1b-9c44-2737be0a572a · inbound

Finite Sample Bounds for Learning with Score Matching cites this paper.

Finite Sample Bounds for Learning with Score Matching Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 1

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-15T04:57:27.149229Z digest=sha256:059b50291831d8724a840a7151fb62040c8fa00bec5eeac0c584ad3df0b10caf

Observation e5bc095e-5de1-4a83-ac9f-ae2a1042f7a2 · 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 Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 1

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verified exact
arxiv_id, observed 2026-08-10T01:08:57.685143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-20T20:49:46.204608Z digest=sha256:e5004035cdc9028cd46cb486a3241cfdc86d6ba1b2540f6a552132e9cc75ec26

Observation e8fddc97-875a-4442-8719-024c3a83f121 · inbound

A note on connections between the F\"ollmer process and the denoising diffusion probabilistic model cites this paper.

A note on connections between the F\"ollmer process and the denoising diffusion probabilistic model Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 1

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-20T00:41:30.640984Z digest=sha256:62dadb2193899fed02690f059ab0d14d4437816a4433fcb2c2af961a466d350d

Observation 6e06263e-b4be-4825-b77d-7fb9a2a94f2c · 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 Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 2

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-21T07:36:09.475575Z digest=sha256:d9791f28d7b55d7e5c4d182ddecd077338770748c00b9d3136970453bbe629a3

Observation 92461ffc-0615-4f4b-8a0b-496fd4ab3863 · inbound

Diffusion-based Denoising Beats Vanilla Score Matching in Parameter Estimation: A Theoretical Explanation cites this paper.

Diffusion-based Denoising Beats Vanilla Score Matching in Parameter Estimation: A Theoretical Explanation Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 2

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-25T05:34:36.228155Z digest=sha256:1a7cf3c69bf47b4ba4eba5c0725686967790f187e3cd73d4272bbf88f856de13

Observation 128cfbfa-5d5e-4c1d-ae41-24363166be5b · inbound

Diffusion Image Generation with Explicit Modeling of Data Manifold Geometry cites this paper.

Diffusion Image Generation with Explicit Modeling of Data Manifold Geometry Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 2

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-29T22:44:39.440271Z digest=sha256:8c94f0ea5e34a10452d2a799b68792d9a2a02a1c80dbca6683d95ac028161d1f

Observation 2d04dca9-5393-4b0e-842d-c77aff8803b4 · inbound

Diffusion Image Generation with Explicit Modeling of Data Manifold Geometry cites this paper.

Diffusion Image Generation with Explicit Modeling of Data Manifold Geometry Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 2

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-07-02T23:11:14.733439Z digest=sha256:87dd4798f6d0099a8b61bc15351100ef8009ed20c50bbf8c52686d04a29cde73

Observation ff22a3b5-76c4-419b-9cd5-61ccedffc64a · inbound

Optimal score function estimation via derivatives constraints cites this paper.

Optimal score function estimation via derivatives constraints Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 4

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-26T18:53:06.962744Z digest=sha256:623d31c74db943fd8ac47319ca45f3561ac72df2efe8e82ec7a8445118831fed

Observation 3ef4ef5c-9b70-42d3-a573-48d443b2fe5e · inbound

Diffusion Models Adapt to Low-Dimensional Structure Under Flexible Coefficient Choices cites this paper.

Diffusion Models Adapt to Low-Dimensional Structure Under Flexible Coefficient Choices Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 2

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arxiv_id, observed 2026-08-10T01:08:57.685143Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-26T05:56:29.406425Z digest=sha256:f822953bc7566e79636301f55e6012cfb75643bbf85de9521f3c671184b8e327

Observation 38c1bf84-c394-4025-ab96-2bd50ef099ef · inbound

Exact simulation of diffusions and improved algorithms for log-concave sampling cites this paper.

Exact simulation of diffusions and improved algorithms for log-concave sampling Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 6

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no resolver link, observed 2026-08-06T11:25:21.022952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T11:25:21.022952Z digest=sha256:90714ea4881597350873c423159f00af9bca28ebb6c639bddcc4b40ff9ba0d35