Paper Citation Record · LEDGER

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network

As of 10 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2604.19240.

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

pith.paper-citation-record.v1
2604.19240 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T02:52:57.713567Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

verified exact3
verified fuzzy31
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8334f959-a35c-46f9-a4aa-c94d94aca1d4 · outbound

This paper cites Image-based surface defect detection using deep learning: A review[J].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Image-based surface defect detection using deep learning: A review[J]

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.040599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 67166883-7578-45e5-b032-f50cd7bf21f1 · outbound

This paper cites Defect image sample generation with GAN for improving defect recognition[J].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Defect image sample generation with GAN for improving defect recognition[J]

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.052898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 43fd1912-282d-4331-a721-8ac15c1f7683 · outbound

This paper cites Few-shot defect image generation via defect-aware feature manipulation[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Few-shot defect image generation via defect-aware feature manipulation[C]

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.044569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6f988caf-f96e-4ad6-8017-994a7e1177e8 · outbound

This paper cites Improved denoising diffusion probabilistic models[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Improved denoising diffusion probabilistic models[C]

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.056552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 414e7c49-9524-4a51-8474-8e47a6293069 · outbound

This paper cites On diffusion modeling for anomaly detection[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network On diffusion modeling for anomaly detection[C]

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.048826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5a64ff8b-ae7e-4485-9330-7b4a3f88c208 · outbound

This paper cites High-resolution image synthesis with latent diffusion models[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network High-resolution image synthesis with latent diffusion models[C]

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.036432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 43bab938-ba72-4f50-8cd9-ef8a2ac189bf · outbound

This paper cites Denoising diffusion implicit models[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Denoising diffusion implicit models[C]

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.063436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e15edd35-8faf-4846-a9df-339205946d80 · outbound

This paper cites Score-based generative modeling through stochastic differential equations[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Score-based generative modeling through stochastic differential equations[C]

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.148458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e077c5e0-89f7-4c6f-8258-314c87418369 · outbound

This paper cites Denoising diffusion probabilistic models[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Denoising diffusion probabilistic models[C]

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T19:01:58.489735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b2c961ab-3a39-48d7-ae97-8e3e4b120a58 · outbound

This paper cites Diffusion models beat GANs on image synthesis[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Diffusion models beat GANs on image synthesis[C]

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T19:01:58.493665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3f95275b-4eac-4a1a-bf91-5310ac11ff15 · outbound

This paper cites A computational approach to edge detection[J].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network A computational approach to edge detection[J]

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T19:01:58.491651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 51dc8b73-2dca-44ce-91b6-6777df91783e · outbound

This paper cites Multiresolution gray-scale and rotation in- variant texture classification with local binary patterns[J].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Multiresolution gray-scale and rotation in- variant texture classification with local binary patterns[J]

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.135890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e992c571-5a61-4220-932e-9d1ed99a673a · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network U-net: Convolutional networks for biomedical image segmentation[C]

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T19:01:58.485163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 46d60d51-4165-43b0-bccc-6700d391289e · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Faster r-cnn: Towards real-time object detection with region proposal networks[C]

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T19:01:58.481133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d565daf0-44ef-40b1-a023-cf2ac02006f6 · outbound

This paper cites Patchcore: Towards total recall in industrial anomaly detection[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Patchcore: Towards total recall in industrial anomaly detection[C]

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.165729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2be10e30-8259-4749-a31f-569a583764b5 · outbound

This paper cites Student-teacher feature pyramid matching for anomaly detection[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Student-teacher feature pyramid matching for anomaly detection[C]

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T19:01:58.483197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9b49038d-7ee4-4808-9bb5-c722b2a6fd07 · outbound

This paper cites Autoaugment: Learning augmentation policies from data[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Autoaugment: Learning augmentation policies from data[C]

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.130863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fa98c67c-031a-477a-ae99-1905d94ae6dc · outbound

This paper cites Randaugment: Practical automated data aug- mentation with a reduced search space[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Randaugment: Practical automated data aug- mentation with a reduced search space[C]

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.142689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 70ac0be6-5edc-487d-a5fe-a51dcb679757 · outbound

This paper cites Defect-gan: High-fidelity defect synthesis for automated defect inspection[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Defect-gan: High-fidelity defect synthesis for automated defect inspection[C]

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.157350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7d93bec1-2b80-4cd6-a180-bd2acdcc5533 · outbound

This paper cites Auto-Encoding Variational Bayes.

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Auto-Encoding Variational Bayes

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-10T02:53:29.241437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 59e8e2a1-2395-4396-a102-e4251f30ca36 · outbound

This paper cites Cutpaste: Self-supervised learning for anomaly detec- tion and localization[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Cutpaste: Self-supervised learning for anomaly detec- tion and localization[C]

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.086597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6cbbb4b3-7550-42b9-98f8-1767d1251f70 · outbound

This paper cites Draem-a discriminatively trained reconstruc- tion embedding for surface anomaly detection[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Draem-a discriminatively trained reconstruc- tion embedding for surface anomaly detection[C]

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.081041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3c9ee465-18ce-4501-aaa9-46435d1ec59b · outbound

This paper cites Diffusionad: Denoising diffusion for anomaly de- tection[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Diffusionad: Denoising diffusion for anomaly de- tection[C]

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.074243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8939e4fa-d28a-4cea-8ee7-2eb76e92d176 · outbound

This paper cites Destseg: Segmentation guided denoising student-teacher for anomaly detection[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Destseg: Segmentation guided denoising student-teacher for anomaly detection[C]

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.068466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3fc2a719-b782-403e-b873-d03c1b6f910e · outbound

This paper cites Winclip: Zero-/few-shot anomaly classification and segmentation[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Winclip: Zero-/few-shot anomaly classification and segmentation[C]

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.125889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fba0445d-e267-473f-97d0-3fe4691623cd · outbound

This paper cites MVTec AD – A comprehensive real-world dataset for unsupervised anomaly detection[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network MVTec AD – A comprehensive real-world dataset for unsupervised anomaly detection[C]

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.109102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 401b02dc-3383-4465-aff9-a0c6f0588b72 · outbound

This paper cites Uninformed students: Student- teacher anomaly detection with discriminative latent features[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Uninformed students: Student- teacher anomaly detection with discriminative latent features[C]

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.114250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 70c0fb0b-b31e-47ed-b2d6-722db80679ce · outbound

This paper cites Anomalous diffusion in umbrella comb.

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network Anomalous diffusion in umbrella comb

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-10T02:53:29.244044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c1826d79-4459-4b72-9e35-12a59598eea1 · outbound

This paper cites SimpleNet: A simple network for image anomaly detection and localization[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network SimpleNet: A simple network for image anomaly detection and localization[C]

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.103420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e4f0b1de-cf3b-4465-a03f-b34aa8ad5d0c · outbound

This paper cites RealNet: A feature selection network with realistic syn- thetic anomaly for anomaly detection[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network RealNet: A feature selection network with realistic syn- thetic anomaly for anomaly detection[C]

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.120888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2e2fa349-4306-45dd-ad6a-1872e9016a40 · outbound

This paper cites CFLOW-AD: Real-time unsupervised anomaly detection with localization via conditional normalizing flows[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network CFLOW-AD: Real-time unsupervised anomaly detection with localization via conditional normalizing flows[C]

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T19:01:58.487826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b0e055f5-bd08-45a8-a4e9-0d1a3c198ae1 · outbound

This paper cites PyramidFlow: High-resolution defect contrastive lo- calization using pyramid normalizing flow[C].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network PyramidFlow: High-resolution defect contrastive lo- calization using pyramid normalizing flow[C]

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.097636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 68f26e52-1234-445d-8fd8-2c9fa9c35e20 · outbound

This paper cites DiAD: A Diffusion-based Framework for Multi-class Anomaly Detection.

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network DiAD: A Diffusion-based Framework for Multi-class Anomaly Detection

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-10T02:53:29.246596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b96feb31-b8b9-473d-aedb-db8e627d96a3 · outbound

This paper cites UTRAD: Anomaly detection and localization with U-Transformer[J].

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network UTRAD: Anomaly detection and localization with U-Transformer[J]

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:57:00.091846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.