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Paper Citation Record · LEDGER

On the Design Fundamentals of Diffusion Models: A Survey

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2306.04542.

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

pith.paper-citation-record.v1
2306.04542 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:03:36.217850Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T23:29:02.125102Z

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 ff16a6bd-03ce-4f03-aa78-5b30b366f4a6 · inbound

$I^2G$: Generating Instructional Illustrations via Text-Conditioned Diffusion cites this paper.

$I^2G$: Generating Instructional Illustrations via Text-Conditioned Diffusion On the Design Fundamentals of Diffusion Models: A Survey

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T15:03:36.217850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:03:36.217850Z digest=sha256:78a5cbdc03c34a2316dc97fffc6bb2fe1dd18b2a6f332d709c4c35e181c7b821

Observation 210275e8-60e1-4a53-9a6a-6c3256369d8c · inbound

REACT: Representation Extraction And Controllable Tuning to Overcome Overfitting in LLM Knowledge Editing cites this paper.

REACT: Representation Extraction And Controllable Tuning to Overcome Overfitting in LLM Knowledge Editing On the Design Fundamentals of Diffusion Models: A Survey

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T14:28:22.378474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:28:22.378474Z digest=sha256:33d28d9044fd6c67e736767cac9f091508a38cc701ab9975beae3b7a6d3578b2

Observation 1e0de972-0b51-484d-ab9d-ef9a6b8bbbb4 · inbound

Rethinking Brain Tumor Segmentation from the Frequency Domain Perspective cites this paper.

Rethinking Brain Tumor Segmentation from the Frequency Domain Perspective On the Design Fundamentals of Diffusion Models: A Survey

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T04:38:08.385443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:38:08.385443Z digest=sha256:8795e22c50d020a2ef7fcf9c4ac7729ecaee18b4d77708df3c725c38e52dfe74

Observation 9fd6ec95-4e6e-4659-8e81-645ef82dc8e9 · inbound

Variational autoencoder for generating realistic $N$-body simulations for dark matter halos cites this paper.

Variational autoencoder for generating realistic $N$-body simulations for dark matter halos On the Design Fundamentals of Diffusion Models: A Survey

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T14:45:34.921164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:45:34.921164Z digest=sha256:6e555f574fead8c79e4be272cc65496dcd15914a670e87da974737c31e7f8b0f

Observation 4039f353-2c57-40bc-8c3d-68a11e750825 · inbound

A Diffusion-based Generative Machine Learning Paradigm for Dynamic Contingency Screening cites this paper.

A Diffusion-based Generative Machine Learning Paradigm for Dynamic Contingency Screening On the Design Fundamentals of Diffusion Models: A Survey

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-18T10:06:13.645404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T10:05:57.747805Z digest=sha256:da11c2f0b0019056f4ed6b79a8e0082b22bedeec4e3364fd4df870803873468a

Observation f4087326-60f7-422d-b8dc-039b4539c5bb · inbound

Quality-Preserving Imperceptible Adversarial Attack on Skeleton-based Human Action Recognition cites this paper.

Quality-Preserving Imperceptible Adversarial Attack on Skeleton-based Human Action Recognition On the Design Fundamentals of Diffusion Models: A Survey

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-07-03T13:58:22.158829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T07:18:00.925914Z digest=sha256:c7f03c9414d781fe4e1b77bd2fd946b907da397b660b5c1011d2f7536371b68b

Observation 62886048-6f0f-4d12-95db-409cee6c16e3 · inbound

Multiscale reconstruction of protein conformations from cryo-EM images cites this paper.

Multiscale reconstruction of protein conformations from cryo-EM images On the Design Fundamentals of Diffusion Models: A Survey

Reference 80

Resolution
verified exact
arxiv_id, observed 2026-07-03T23:29:02.127253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-26T22:19:50.914673Z digest=sha256:394a7fa8c57b1412502b1241936ffacf30ae972716cacfe3d791cb047ed1c146