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Paper Citation Record · LEDGER

Non Gaussian Denoising Diffusion Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2106.07582.

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

pith.paper-citation-record.v1
2106.07582 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:01:49.663095Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T05:36:00.803510Z

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 9ef81dca-8ab4-4f9a-85be-71701ee6fcdb · inbound

Progressive Distillation for Fast Sampling of Diffusion Models cites this paper.

Progressive Distillation for Fast Sampling of Diffusion Models Non Gaussian Denoising Diffusion Models

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:37:44.688792Z

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=pdf_text observed=2026-05-11T09:37:44.394785Z digest=sha256:69fec54c12308c586b0296b2201be00a11c8363cc39d2d4c362846000faacb2a

Observation 68203407-175c-42e0-938d-f6e23764ecf4 · inbound

Improved DDIM Sampling with Moment Matching Gaussian Mixtures cites this paper.

Improved DDIM Sampling with Moment Matching Gaussian Mixtures Non Gaussian Denoising Diffusion Models

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-24T05:36:00.806794Z

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=pdf_text observed=2026-05-24T05:34:56.939751Z digest=sha256:6220387a098fdb13c95817d03326f4806af0de7160c94cab74e6e2d43ffc6794

Observation d3fe70ab-e0ba-46bb-aae8-7114bfedaa12 · inbound

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models cites this paper.

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models Non Gaussian Denoising Diffusion Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:49.663095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:49.663095Z digest=sha256:96c6351e7b2a49b36be731eb0121cfa670d6ba146476115a1f57b034fb46fb65

Observation 7e1bfb33-985b-4e87-b6f7-aab66d0184a8 · inbound

HyperNet-Adaptation for Diffusion-Based Test Case Generation cites this paper.

HyperNet-Adaptation for Diffusion-Based Test Case Generation Non Gaussian Denoising Diffusion Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-03T09:04:37.178843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T09:04:37.178843Z digest=sha256:5d95fef57b7972720d9180517e5c72052b3a4d61852dc3f2817f0e8a7786dc14

Observation 15faa784-be4d-49cf-a63e-79cd04accfc2 · inbound

Mat\'ern Noise for Triangulation-Agnostic Flow Matching on Meshes cites this paper.

Mat\'ern Noise for Triangulation-Agnostic Flow Matching on Meshes Non Gaussian Denoising Diffusion Models

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T02:58:00.303281Z

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=2026-05-20T02:53:56.937465Z digest=sha256:a92d1f77e58dcf38e4dd8187dba6076b9bee9446a5d391b654e7846f9efc621b

Observation b9873110-95c2-4b75-9d48-8b8c6dc1d0b7 · inbound

Pseudorandom Streams within Diffusion Models Act as Learnable Inputs That Affect Generation Quality cites this paper.

Pseudorandom Streams within Diffusion Models Act as Learnable Inputs That Affect Generation Quality Non Gaussian Denoising Diffusion Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-04T04:32:10.446297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T04:32:10.446297Z digest=sha256:1d9fa5de05ad7c6fa7c5fbd9e15460d14564cf2db7e31d160579713e336f08dc