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Paper Citation Record · LEDGER

Your diffusion model secretly knows the dimension of the data manifold

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2212.12611.

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

pith.paper-citation-record.v1
2212.12611 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:02:04.448653Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:19:12.839812Z

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 3d44789d-aa58-4eab-bdc3-afaff392b66a · inbound

On the Local Complexity of Linear Regions in Deep ReLU Networks cites this paper.

On the Local Complexity of Linear Regions in Deep ReLU Networks Your diffusion model secretly knows the dimension of the data manifold

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T05:02:04.448653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:02:04.448653Z digest=sha256:6a83d70bca1a9000e1f57a2318168d8b29195347b957a14c159e8b919ad9e55b

Observation be0d848f-b894-4d7f-899b-f2693cdda6b7 · inbound

Exploring Time Conditioning in Diffusion Generative Models from Disjoint Noisy Data Manifolds cites this paper.

Exploring Time Conditioning in Diffusion Generative Models from Disjoint Noisy Data Manifolds Your diffusion model secretly knows the dimension of the data manifold

Reference 74

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:31:15.602876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-07T16:52:29.681159Z digest=sha256:ee9511559ba9a5979b1173e34088d448120ae05a1e963e31a402d2e552290471

Observation 7bd72f8a-4555-4046-8ece-21239cecf3de · inbound

Style-CCL: Content-Preserving Style Transfer via Curriculum Continual Learning cites this paper.

Style-CCL: Content-Preserving Style Transfer via Curriculum Continual Learning Your diffusion model secretly knows the dimension of the data manifold

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-04T00:19:12.841881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-04T00:12:14.850098Z digest=sha256:81a9731501bc108a5ec6f970be3958864765489cf1abbc61041af3950eb8abeb

Observation e96e59a8-aff8-48d3-915c-a216145c76a1 · inbound

MUSE: Unlocking Timestep as Native Task Steering for One-Step Dense Prediction cites this paper.

MUSE: Unlocking Timestep as Native Task Steering for One-Step Dense Prediction Your diffusion model secretly knows the dimension of the data manifold

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-06-30T06:24:19.401599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-30T06:17:53.096700Z digest=sha256:d92264c19a1025614d234bdb607e1032e2a11f9c9b7000d4d3bc94a29cfccc36

Observation 4bc0407f-b0e4-4616-bcd5-147a09f8a0ed · inbound

Diffusion models recover accurate mixture weights despite score function insensitivity cites this paper.

Diffusion models recover accurate mixture weights despite score function insensitivity Your diffusion model secretly knows the dimension of the data manifold

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-01T23:23:44.758878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T23:23:44.758878Z digest=sha256:84ab1e0597bf95948e116c694673c88b75a3836bc84135168929e5d8739b1677