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Paper Citation Record · LEDGER

Accelerating Convergence of Score-Based Diffusion Models, Provably

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2403.03852.

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

pith.paper-citation-record.v1
2403.03852 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 2026-08-19T06:32:44.657259+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:04:00.072135Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T12:49:52.511075Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
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  • 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 2640df79-a445-408c-8c0e-143345100ad9 · inbound

On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality cites this paper.

On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-12T12:06:13.427234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:06:13.427234Z digest=sha256:ee04ccee55b70381db62a0913563e0d8ddbd753eb6a5520295e7bcb54e20bbcb

Observation 1e265695-08d9-46b6-b9f5-becdedac8130 · inbound

Fokker-Planck to Callan-Symanzik: evolution of weight matrices under training cites this paper.

Fokker-Planck to Callan-Symanzik: evolution of weight matrices under training Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T19:54:05.551393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:54:05.551393Z digest=sha256:1ab28f830dc4bacd51aca6a2aa53c48fa3021b615cdfc4c86c5d0cde2f453ed2

Observation 224ccd9d-d9b3-42a2-b48a-36ed970463f6 · inbound

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

Low-dimensional adaptation of diffusion models: Convergence in total variation Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-10T16:42:26.440785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:42:26.440785Z digest=sha256:2de118b45e51b9940d9cdf5fef2cc4b3f89f54948026e5a94957b85bd20b3104

Observation c057c70d-907d-4cd2-9e36-1e42d57e24b1 · 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 Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-09T22:27:37.448643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T22:27:37.448643Z digest=sha256:a02e419ab7de365470f3e1dafc04ac812bd9786dc79a0f5a866da102e8cb0307

Observation d92df92d-a465-46d9-ab5b-85c0d5250edf · inbound

Advancing Wasserstein Convergence Analysis of Score-Based Models: Insights from Discretization and Second-Order Acceleration cites this paper.

Advancing Wasserstein Convergence Analysis of Score-Based Models: Insights from Discretization and Second-Order Acceleration Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-08T21:18:48.840029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T21:18:48.840029Z digest=sha256:b057004041d03ce66f114e74f6fbffd36c07f09e24a093073f0ad318ae6e9efc

Observation be1d985d-ff91-4a07-b2eb-e9bf7f5babe6 · inbound

Convergence Of Consistency Model With Multistep Sampling Under General Data Assumptions cites this paper.

Convergence Of Consistency Model With Multistep Sampling Under General Data Assumptions Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T00:04:00.072135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:04:00.072135Z digest=sha256:bdb6740be6a38d7ff6fc46ce890271f4de5276477702eb4f0859afd001c48b7f

Observation 8bab2d47-a4eb-4a72-b2d0-e97e071348bb · inbound

Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach cites this paper.

Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 169

Resolution
unresolved
no resolver link, observed 2026-08-07T10:54:50.248988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:54:50.248988Z digest=sha256:4c05a8a806cfead46b926e9581d91921dc06aee5ffc13abc0f503ba778d2e05f

Observation e922d2f6-68f1-4750-90b5-59f819efd3c3 · 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 Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T00:49:46.052589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:49:46.052589Z digest=sha256:f19858a717fe9d3bfb63626a87f7c7db4c9f9c645bcb14c92c4bd2eb7ac72af4

Observation 7ac54f9f-21a1-4fa0-b5bf-6a26c26606e7 · inbound

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

Faster Diffusion Models via Higher-Order Approximation Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T21:45:14.385738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:45:14.385738Z digest=sha256:2a4ae8817c4a87de454728359d908353e2f926b123206a0dba33a9f27fdc66fb

Observation 5af8fe6c-1b75-4580-ac01-c182a7c850b4 · inbound

Likelihood Matching for Diffusion Models cites this paper.

Likelihood Matching for Diffusion Models Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T04:26:45.685549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:26:45.685549Z digest=sha256:fd760f248acf8c866af084f0e0b8c2d289701a627b081fac4a7d429db5ddcfa9

Observation d0b5b71f-d29a-40b6-81a4-5c433dc95956 · inbound

Non-asymptotic convergence bound of conditional diffusion models cites this paper.

Non-asymptotic convergence bound of conditional diffusion models Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-05T20:56:33.442850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T20:56:33.442850Z digest=sha256:2cb5383e03ce4a21723e08a5d9a3aa371b9673ab16ae19e880539e76320ac01a

Observation 065c7cef-27ee-4af8-b262-1c1ea20a603a · inbound

Lipschitz-Guided Design of Interpolation Schedules in Generative Models cites this paper.

Lipschitz-Guided Design of Interpolation Schedules in Generative Models Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-21T21:54:22.843207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-21T21:53:15.115078Z digest=sha256:82851124beb1bb5c4ec87bfc5bbb76fd5df1f4452a6bf376a61b9ea57ec8760e

Observation 2a021546-c801-4606-81ef-a0df7f58e7be · inbound

Provable Diffusion Posterior Sampling for Bayesian Inversion cites this paper.

Provable Diffusion Posterior Sampling for Bayesian Inversion Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-03T17:55:18.718852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T17:55:18.718852Z digest=sha256:4b7de22a686942c449f87c4179b010035ed55a1c914e42ffe0c2433345d33b6d

Observation d5f00b5c-29d1-4b27-957d-a6cbed9e3d11 · inbound

Proximal-Based Generative Modeling for Bayesian Inverse Problems cites this paper.

Proximal-Based Generative Modeling for Bayesian Inverse Problems Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 51

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T17:57:33.540984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-14T17:53:42.816596Z digest=sha256:4a6ec03f1665b8b464b0a9c14430ec1232a647bb8e66229d32d4dc4ddb65dd6e

Observation c6b241ae-3f9f-498a-a0dc-298ef993b183 · 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 Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-07-04T12:49:52.512638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-06-26T05:56:29.406425Z digest=sha256:45c7c059f65ba4a422eabc0026fe74b39a681a06fd4b6f2a7e311f65a831d933