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Paper Citation Record · LEDGER

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment

As of 7 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 1 inbound Pith citation observation for arXiv:2509.06693.

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

pith.paper-citation-record.v1
2509.06693 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T23:20:42.624533Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T04:05:22.253489Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T17:15:50.949342Z

Reference resolution

39 of 39 outbound references displayed

  • verified exact3
  • verified fuzzy30
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c4c5417e-4166-4fff-bcc9-c3a097902cb5 · outbound

This paper cites Supervised anomaly detection for complex industrial images,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Supervised anomaly detection for complex industrial images,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.629844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation fa8bea9c-c017-4542-9570-2ce17b4c69be · outbound

This paper cites Shape-guided dual-memory learning for 3D anomaly detection,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Shape-guided dual-memory learning for 3D anomaly detection,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.623099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:39.555740Z digest=sha256:5b390adb90c9203a46aa404fae24c5ca4651f26115e209f6c43cff7696e5bc76

Observation cc00e53d-ade3-4c79-a91f-7bd1a31cb711 · outbound

This paper cites Latent outlier exposure for anomaly detection with contaminated data,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Latent outlier exposure for anomaly detection with contaminated data,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.615292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e3147825-2694-437b-b587-b886ecd42bb2 · outbound

This paper cites Cutpaste: Self- supervised learning for anomaly detection and localization,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Cutpaste: Self- supervised learning for anomaly detection and localization,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.513553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:39.719543Z digest=sha256:8a96a473ff9f8a142b1f30d949a3f77ac66851792ad0b799cf48da6ccfa89ed8

Observation 27bdc264-fc81-4392-8b0f-7191267c77da · outbound

This paper cites Draem-a discrimi- natively trained reconstruction embedding for surface anomaly detection,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Draem-a discrimi- natively trained reconstruction embedding for surface anomaly detection,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.507933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:39.801433Z digest=sha256:a4fc8446f037c2bb7173146434cfb8961a3e3509dc5cecf046585da79a05b36f

Observation 613dc004-1ee5-461a-a49e-d388a9e60d42 · outbound

This paper cites Few-shot defect image generation via defect-aware feature manipulation,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Few-shot defect image generation via defect-aware feature manipulation,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.500620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:39.913092Z digest=sha256:2cc6f1e6519742aee88dff6ee5dbfd4b93d5930403f72c92793b7a10b29ed4c9

Observation f7db7d2f-4316-4639-9739-10a62c07a615 · outbound

This paper cites Anomalydiffusion: Few-shot anomaly image generation with diffusion model,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Anomalydiffusion: Few-shot anomaly image generation with diffusion model,

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.492704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:39.984328Z digest=sha256:4d5fdae7ccd9df2effbd8520ea84c877fae435089e993bb4be5ae5c0212bbf77

Observation 32c65218-5519-4cfb-8e94-2b5420b42fec · outbound

This paper cites Defect image sample generation with gan for improving defect recognition,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Defect image sample generation with gan for improving defect recognition,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.485197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:40.094551Z digest=sha256:284831472c3c5a8b5895a51ed15070b05338ff2418775302332de85639ad0e43

Observation 55e1adcd-4fd4-45fa-8dde-264df879ba2a · outbound

This paper cites Multistage gan for fabric defect detection,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Multistage gan for fabric defect detection,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.477589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:40.169935Z digest=sha256:10b7762d849350332a7e07b6811c4809d2356e172dc9ca44975220551bdb250a

Observation 91d0a020-0a68-4314-b546-5fd366836343 · outbound

This paper cites Repaint: Inpainting using denoising diffusion probabilistic models,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Repaint: Inpainting using denoising diffusion probabilistic models,

Reference 10

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raw_fallback, observed 2026-08-04T23:20:45.471400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:40.274595Z digest=sha256:ea39d68f10e5adab4f47fe259881d6dde194ea255092373b9e64c7cce786be82

Observation d623f2d6-3023-4378-96c5-6a35f4e52603 · outbound

This paper cites Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-04T23:20:40.369817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:20:40.369817Z digest=sha256:eee913bdd35e0d797c9d642905ae73a8047442b7362789c29f677ceb5caac25b

Observation dadcb4e6-9381-4b5d-952d-f1e7e3ee7248 · outbound

This paper cites Defect spectrum: a granular look of large-scale defect datasets with rich semantics,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Defect spectrum: a granular look of large-scale defect datasets with rich semantics,

Reference 12

Resolution
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raw_fallback, observed 2026-08-04T23:20:45.464873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:40.442358Z digest=sha256:c89901ef7c4e5f403f9f0351ad3228b535b35c1311f50d64c709269662ec96c4

Observation 8d953937-af3c-478d-9a7a-313eea386389 · outbound

This paper cites Reb: Reducing biases in representation for industrial anomaly detection,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Reb: Reducing biases in representation for industrial anomaly detection,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.456736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:40.533334Z digest=sha256:8e4d78b4604cdc8000600cda30343a823c74a86f26f2a758bd2740730c0e5574

Observation 855179ca-0a0a-4f81-a982-af81d149079e · outbound

This paper cites Destseg: Segmentation guided denoising student-teacher for anomaly detection,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Destseg: Segmentation guided denoising student-teacher for anomaly detection,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.450304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:40.613436Z digest=sha256:9261dd7eca2505eecccaa7b70919538826caf198daf58209911dac2d1e9574fa

Observation 52175849-0857-4385-8d24-5d4c3b3c1e13 · outbound

This paper cites Defect-gan: High- fidelity defect synthesis for automated defect inspection,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Defect-gan: High- fidelity defect synthesis for automated defect inspection,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.443637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:40.704185Z digest=sha256:0cc42ad12f84f22129862a94dc6f012e53638dbb8de7059c92c817697e2b8bdc

Observation 76c8cbe2-8623-4716-b11e-048bb00bf383 · outbound

This paper cites A new contrastive gan with data augmentation for surface defect recognition under limited data,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment A new contrastive gan with data augmentation for surface defect recognition under limited data,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.435380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:40.800168Z digest=sha256:b7fdfeec8385bc6db2a94bb01d684fe69ccbe00acf6102654de13b1bfca0dd86

Observation b1ecf4fc-72b1-4528-8698-f236d78dfae3 · outbound

This paper cites SeaS: Few-shot Industrial Anomaly Image Generation with Separation and Sharing Fine-tuning.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment SeaS: Few-shot Industrial Anomaly Image Generation with Separation and Sharing Fine-tuning

Reference 17

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unresolved
no resolver link, observed 2026-08-04T23:20:40.848468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a2f57274-ac7b-472b-a0c0-3ba1d72850a6 · outbound

This paper cites Unseen Visual Anomaly Generation.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Unseen Visual Anomaly Generation

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-04T23:20:43.133968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:40.953749Z digest=sha256:90575fb21e98c3441347abf05075aab920de287e2bf8f6f8af791c4f21260d46

Observation 45c5b61c-61d6-4231-acba-f81a44b7376c · outbound

This paper cites Few-shot defect image generation based on consistency modeling,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Few-shot defect image generation based on consistency modeling,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.428450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:41.036003Z digest=sha256:01bc355e672dc13a442b6ba921bce218f03397d38b5805f84ab4364456b13302

Observation ea951715-8674-4dad-aac8-39b3889113a4 · outbound

This paper cites DictAS: A Framework for Class-Generalizable Few-Shot Anomaly Segmentation via Dictionary Lookup.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment DictAS: A Framework for Class-Generalizable Few-Shot Anomaly Segmentation via Dictionary Lookup

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-04T23:20:42.957200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:41.133891Z digest=sha256:eaac3bef9b05c32cc1b8aca710445e69f1854675771a6385a24e865c4ee485ac

Observation f7000993-dbe8-4c0a-bfec-c152dc045681 · outbound

This paper cites Fascinating supervisory signals and where to find them: Deep anomaly 13 detection with scale learning,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Fascinating supervisory signals and where to find them: Deep anomaly 13 detection with scale learning,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.421399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:41.195714Z digest=sha256:595df98cd589b9cf97fe51cfcdfb577f6083b4ff7418dda62a7958ef50a4a93e

Observation a6bfde44-8c0f-49bc-8ba7-baf4b379049b · outbound

This paper cites Reconstruction by inpainting for visual anomaly detection,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Reconstruction by inpainting for visual anomaly detection,

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-04T23:20:41.282292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:20:41.282292Z digest=sha256:ee1ce101eb723e31557716dbae0e0e949e46c84418b9bb8deee03e5865022222

Observation 2093577f-7a56-4cd5-ae90-7d796c12e057 · outbound

This paper cites Rethinking reconstruction autoencoder-based out-of- distribution detection,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Rethinking reconstruction autoencoder-based out-of- distribution detection,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.409302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:41.378129Z digest=sha256:214c38e3b149c4af4a8221884e39c9adc760fcef12818eb60e99b012531a88fe

Observation c8b0b131-31ad-43e2-aaa4-bcab41767801 · outbound

This paper cites Dual-modeling decouple distillation for unsupervised anomaly detection,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Dual-modeling decouple distillation for unsupervised anomaly detection,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.326707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:41.471861Z digest=sha256:ab4f3881c43e415a8c608d95cc1a4dfd6733d1505b358e7b1f32940a1b6f2235

Observation 20d87ebf-7ee0-4e81-92dd-c79e9710bedb · outbound

This paper cites Slsg: Industrial image anomaly detection with improved feature embeddings and one- class classification,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Slsg: Industrial image anomaly detection with improved feature embeddings and one- class classification,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:45.144117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:41.562471Z digest=sha256:1597b939f1685e7055005430da5adf07eafe82364c7fec3e7fd851d1a06d3269

Observation 2d613f11-ecb7-473e-a747-46c5a06744de · outbound

This paper cites Progressive boundary guided anomaly synthesis for industrial anomaly de- tection,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Progressive boundary guided anomaly synthesis for industrial anomaly de- tection,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:44.914729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:41.616327Z digest=sha256:b31d930a060e2145ae8e19625fa3bd2b6e7d470eb5c2316348f2814dbcfab32e

Observation e26f14c2-a91b-4dbe-9e3e-5871d327c862 · outbound

This paper cites A unified anomaly synthesis strategy with gradient ascent for industrial anomaly detection and localization,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment A unified anomaly synthesis strategy with gradient ascent for industrial anomaly detection and localization,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:44.784915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:41.694177Z digest=sha256:2b67a8faeb36070f5a8b99b48e52d4cb33bd0dc69984af8310f0fcc55c0bf089

Observation a3099c26-c45d-494f-ae69-8e054fba89c4 · outbound

This paper cites Synth4Seg -- Learning Defect Data Synthesis for Defect Segmentation using Bi-level Optimization.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Synth4Seg -- Learning Defect Data Synthesis for Defect Segmentation using Bi-level Optimization

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-04T23:20:42.795032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:41.783195Z digest=sha256:2a23710ce1d60fe899bb1a50663ef8c4f3905f00cfeceb9e2b663eb606cf0093

Observation 849212a1-5dfb-4ae7-9ced-29da1be22673 · outbound

This paper cites High-resolution image synthesis with latent diffusion models,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment High-resolution image synthesis with latent diffusion models,

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-04T23:20:41.865064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:20:41.865064Z digest=sha256:041bb660e322fb6f9954f567af9d8ce888b42e0bbb4e2733da9504efb53dfe68

Observation 49290bad-f3e8-4b5c-bd6b-0758f793e007 · outbound

This paper cites Score-based generative modeling through stochastic differential equations,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Score-based generative modeling through stochastic differential equations,

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-04T23:20:41.923571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:20:41.923571Z digest=sha256:4479246b089ff35c63877eec427dc725f88fd2b6e9a3680d209e23e14fba2d3c

Observation 3f378625-fe83-41a9-95f6-78cd6342d756 · outbound

This paper cites Convergence of score-based gener- ative modeling for general data distributions,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Convergence of score-based gener- ative modeling for general data distributions,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:44.592282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:42.038878Z digest=sha256:c26c614179f3f4e61e1a4c8ff3159cc08f268e761a1e7512607f947abe53634e

Observation 44728966-4d4b-4272-b439-27e6416f6102 · outbound

This paper cites Theory of consistency diffusion models: Distribution estimation meets fast sampling,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Theory of consistency diffusion models: Distribution estimation meets fast sampling,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:44.324973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:42.097105Z digest=sha256:03ac98b60af31971c0e4773dec78be16d751cebe1757c8b49c67fcbf46bab14f

Observation 76de2e55-e52c-4437-9de1-77e40b0a0b44 · outbound

This paper cites Sampling is as easy as keeping the consistency: convergence guarantee for consistency models,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Sampling is as easy as keeping the consistency: convergence guarantee for consistency models,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:44.045073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:42.177742Z digest=sha256:1cf30f7024881758d81714949ec892b7ada789de5a8b461e19123ad40e078210

Observation d194710a-2262-41da-8689-34c97bffa2bf · outbound

This paper cites Mvtec ad– a comprehensive real-world dataset for unsupervised anomaly detection,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Mvtec ad– a comprehensive real-world dataset for unsupervised anomaly detection,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:43.877652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:42.234178Z digest=sha256:f11ceb57bc52539714b8247a6148c4873bbd14766862c4026f5d5f974870a872

Observation 186f0f9d-7941-48ad-897c-27e33a2fbacd · outbound

This paper cites VT-ADL: A vision transformer network for image anomaly detection and localization,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment VT-ADL: A vision transformer network for image anomaly detection and localization,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:43.706598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:42.320175Z digest=sha256:8a409348cb8fff4a8e3963070a553e5ea3b48ce623e7414a6e798dabac11e3d0

Observation 987646a0-85e5-47fa-a98a-a0becf301fae · outbound

This paper cites Realnet: A feature selection network with realistic synthetic anomaly for anomaly detection,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Realnet: A feature selection network with realistic synthetic anomaly for anomaly detection,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:43.548016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:42.399690Z digest=sha256:7e70a522a7e6ec5c88823e6c5be4c10685f3fd31ada920e0958b5d6ea6bdc8d1

Observation 3a73767d-b8d9-4678-8ee6-4ff21b80d835 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transformers,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Segformer: Simple and efficient design for semantic segmentation with transformers,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-04T23:20:42.485376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:20:42.485376Z digest=sha256:6c92f9c9e116fcc1b824259b309a6cfb7417160c27ab97a0e2b2dea523542348

Observation 6ed1a31a-173d-4d67-b29f-882c24a9dae1 · outbound

This paper cites Bisenet v2: Bilateral network with guided aggregation for real-time semantic segmentation,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Bisenet v2: Bilateral network with guided aggregation for real-time semantic segmentation,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:43.412676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:42.573008Z digest=sha256:682ff09226b8795e7e2450e93735b5ff9b28c79ff484d0a759ff39c8696d8631

Observation 90b2c179-7f63-4ceb-ad8f-d09fbd68934c · outbound

This paper cites Rethinking bisenet for real-time semantic segmentation,.

STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment Rethinking bisenet for real-time semantic segmentation,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:20:43.301819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T23:20:42.624533Z digest=sha256:22d718297cae7b380c65a47fc5b44723164268fc040a5b4b7def8467093b9c36

Pith citing papers

Observation a440ef38-b7e2-43e1-a2af-28ff728dc1ad · inbound

Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation cites this paper.

Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment

Reference 79

Resolution
verified exact
arxiv_id, observed 2026-07-01T17:15:50.950911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-29T04:05:22.253489Z digest=sha256:931d398af2cbfa04afc8f77aa5060407108afbcaa3f7ab100dcae5acce01c2c5