Paper Citation Record · LEDGER

DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2303.08730.

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

pith.paper-citation-record.v1
2303.08730 v4

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 2026-08-07T13:21:03.173909Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T19:53:55.256209Z

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 8dfdb32b-a9dd-4dad-bf80-82bd0b891742 · inbound

OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning cites this paper.

OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T13:21:03.173909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b698dc9-d402-4b2d-acdf-89ddd56996c5 · inbound

Anomalies by Synthesis: Anomaly Detection using Generative Diffusion Models for Off-Road Navigation cites this paper.

Anomalies by Synthesis: Anomaly Detection using Generative Diffusion Models for Off-Road Navigation DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-07T13:06:39.856136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06a235d2-6d7b-4a27-be9e-2a13e827aba5 · inbound

Quality-Aware Language-Conditioned Local Auto-Regressive Anomaly Synthesis and Detection cites this paper.

Quality-Aware Language-Conditioned Local Auto-Regressive Anomaly Synthesis and Detection DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T04:29:22.558082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a8960dc-8b8f-44f1-9177-ed9f24c14839 · inbound

ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction cites this paper.

ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T21:42:32.990372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a310ba0-8d1c-46d3-b920-e1357f8a8957 · inbound

IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools cites this paper.

IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:33:58.388077Z

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.

Observation c779614d-e467-482c-8c4a-aa1102531350 · inbound

Diffuse to Detect: Generative Diffusion Models for Unsupervised IC Anomaly Detection cites this paper.

Diffuse to Detect: Generative Diffusion Models for Unsupervised IC Anomaly Detection DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-29T19:53:55.257716Z

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.