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Paper Citation Record · LEDGER

Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2409.20124.

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

pith.paper-citation-record.v1
2409.20124 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:56:33.452208Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T19:37:19.428759Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • 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 7f420824-6290-4fe2-90e6-febf97f33bd8 · inbound

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

Non-asymptotic convergence bound of conditional diffusion models Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-05T20:56:33.452208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T20:56:33.452208Z digest=sha256:e23cef1dca6843e18f78f1ce465db27c500bc41b4c53c2bf68e46ce7fa688944

Observation f509dec3-f20f-482b-a207-6ba1e1cf31fb · inbound

Provable Diffusion Posterior Sampling for Bayesian Inversion cites this paper.

Provable Diffusion Posterior Sampling for Bayesian Inversion Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation

Reference 131

Resolution
unresolved
no resolver link, observed 2026-08-03T17:55:21.613085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T17:55:21.613085Z digest=sha256:e49f9861f2657b87ff202c05ecd644f96b5ac979c7c9d6198ebccd0539c3171e

Observation 8ce66746-1de4-401b-a93a-e901182230ae · inbound

Can Generative Artificial Intelligence Survive Data Contamination? Theoretical Guarantees under Contaminated Recursive Training cites this paper.

Can Generative Artificial Intelligence Survive Data Contamination? Theoretical Guarantees under Contaminated Recursive Training Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-02T22:51:31.190156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T22:51:31.190156Z digest=sha256:ccedbf18848e588618218c3cbfcd4999fd8f17ca664bd348a8d585e2f28fc974

Observation 0ad7b8cd-f762-4dbc-8181-9e4d5cc2acfc · inbound

Testing Equality of Conditional Distributions via Generative Models cites this paper.

Testing Equality of Conditional Distributions via Generative Models Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation

Reference 176

Resolution
verified exact
arxiv_id, observed 2026-07-02T19:37:19.430937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T21:25:10.038196Z digest=sha256:fa201680d6d9535fdbcf99221ab3cd529df3d23361f683748e38032e37980025