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Paper Citation Record · LEDGER

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection

As of 22 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 5 inbound Pith citation observations for arXiv:2505.06603.

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

pith.paper-citation-record.v1
2505.06603 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:42:38.248718Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:47:37.258947Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T12:49:52.970966Z

Reference resolution

43 of 43 outbound references displayed

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  • unresolved6
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4dcc8758-1e2e-42ca-b246-84d6de58c7d4 · outbound

This paper cites Memory aware synapses: Learning what (not) to forget.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Memory aware synapses: Learning what (not) to forget

Reference 1

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 5bee3ef1-bd19-44d9-b328-5efd71f01b9b · outbound

This paper cites Disentangling writer and character styles for hand- writing generation.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Disentangling writer and character styles for hand- writing generation

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation afefde0a-40b3-4144-8d1c-27656faaf2f7 · outbound

This paper cites Ddgr: Con- tinual learning with deep diffusion-based generative re- play.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Ddgr: Con- tinual learning with deep diffusion-based generative re- play

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation bafae42c-eb15-43a7-b62f-0026e9d9b315 · outbound

This paper cites MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:42:38.052484Z digest=sha256:949018159b1b3b21bb29bf420acae21a8fbe8818951d4de7ad72cd6947a44874

Observation 651efc8d-7cc8-4548-a81d-65bb87ac058a · outbound

This paper cites Learn- ing unified reference representation for unsupervised multi-class anomaly detection.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Learn- ing unified reference representation for unsupervised multi-class anomaly detection

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation a4439486-d029-4716-8219-a9516a1800c6 · outbound

This paper cites En- hancing table structure recognition via bounding box guid- ance.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection En- hancing table structure recognition via bounding box guid- ance

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation a04c6e2e-85ea-47ca-9593-cb1d89d749cb · outbound

This paper cites Anomalydiffusion: Few-shot anomaly image gen- eration with diffusion model.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Anomalydiffusion: Few-shot anomaly image gen- eration with diffusion model

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 10c4b388-abde-4858-9367-5bc1b66f76ed · outbound

This paper cites Segment anything.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Segment anything

Reference 14

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation a73cc475-3cc4-404d-9190-84a8a3f8d3a5 · outbound

This paper cites Overcom- ing catastrophic forgetting in neural networks.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Overcom- ing catastrophic forgetting in neural networks

Reference 15

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no resolver link, observed 2026-08-15T22:42:38.097124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:42:38.097124Z digest=sha256:920c6d6cd83c1880d486fc022fa0af0fc92cc99083be3283afef92237cccbddd

Observation 93a12998-b2e2-43a9-9eab-27be9f57b05a · outbound

This paper cites Comprehensive generative replay for task- incremental segmentation with concurrent appearance and semantic forgetting.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Comprehensive generative replay for task- incremental segmentation with concurrent appearance and semantic forgetting

Reference 18

Resolution
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raw_fallback, observed 2026-08-15T22:42:38.639969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 824cc95e-8f95-4db6-985a-cee15ea6607c · outbound

This paper cites One-for-More: Continual Diffusion Model for Anomaly Detection.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection One-for-More: Continual Diffusion Model for Anomaly Detection

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-15T22:42:38.116321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:42:38.116321Z digest=sha256:82779872f2358957aaa8aec08a99563c975538dc4f2e5c1d12ea7ae24b123fe8

Observation 46ef32b7-cf63-47cb-aee7-5d0fe5b8e2ae · outbound

This paper cites Diffusion-driven data replay: A novel approach to combat forgetting in feder- ated class continual learning.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Diffusion-driven data replay: A novel approach to combat forgetting in feder- ated class continual learning

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.626034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 33ce1710-b68c-47b8-af7f-7fc6e37f6419 · outbound

This paper cites Generative feature replay for class-incremental learning.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Generative feature replay for class-incremental learning

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 16521cbf-4e2e-4e87-bfaf-7cc1bb319c4d · outbound

This paper cites Packnet: Adding multiple tasks to a single net- work by iterative pruning.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Packnet: Adding multiple tasks to a single net- work by iterative pruning

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.588120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 45bb14c1-6563-4663-8788-18812745ab2e · outbound

This paper cites Piggyback: Adapting a single network to multiple tasks by learning to mask weights.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Piggyback: Adapting a single network to multiple tasks by learning to mask weights

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.574675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation fd86cfc0-942c-4b24-b6cb-cb35e9e98c45 · outbound

This paper cites Continual deep learning by functional regularisation of memorable past.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Continual deep learning by functional regularisation of memorable past

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.558045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 5a49eec6-a1b5-4779-bbb9-d86fd0a4366a · outbound

This paper cites Globally correlation-aware hard negative gener- ation.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Globally correlation-aware hard negative gener- ation

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.545375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 1c70775e-7233-49d4-a28d-e83192cf4dc7 · outbound

This paper cites icarl: Incremental classifier and representation learning.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection icarl: Incremental classifier and representation learning

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.532154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 84e0ac25-52ed-4097-8f98-74ee3635dac2 · outbound

This paper cites Panda: Adapting pretrained features for anomaly detection and segmentation.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Panda: Adapting pretrained features for anomaly detection and segmentation

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.519317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 32c7537f-e3b5-43ba-9b2e-2e47d6f90f32 · outbound

This paper cites Scalable recollec- tions for continual lifelong learning.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Scalable recollec- tions for continual lifelong learning

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.505867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 3a9aa9e0-b780-4d45-a460-665eadf51fd9 · outbound

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

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection High-resolution image synthesis with latent diffusion models

Reference 30

Resolution
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no resolver link, observed 2026-08-15T22:42:38.175511Z

Source-reported events for the cited work

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Observation ed661bef-35a1-46f2-a5a5-9b3a73825f0f · outbound

This paper cites Towards total recall in industrial anomaly detec- tion.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Towards total recall in industrial anomaly detec- tion

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.486034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f16c9a4a-ffb8-470f-bf00-6a562d9d6eef · outbound

This paper cites Continual learning with deep gener- ative replay.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Continual learning with deep gener- ative replay

Reference 32

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 9a22421b-857b-4ee3-b8cb-0144f5785c5c · outbound

This paper cites An incre- mental unified framework for small defect inspection.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection An incre- mental unified framework for small defect inspection

Reference 33

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.191167Z digest=sha256:912296c552a1a04dcd6d0d3336c2c925b27fd25a40b7b2b8e739c0edbbd62228

Observation 4beaa783-970a-4a13-9ef9-6780007ce2dc · outbound

This paper cites Ordisco: Ef- fective and efficient usage of incremental unlabeled data for semi-supervised continual learning.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Ordisco: Ef- fective and efficient usage of incremental unlabeled data for semi-supervised continual learning

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.450205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation a0b038ca-97cb-4277-9391-3cd13f42994d · outbound

This paper cites Unsu- pervised anomaly detection via masked diffusion posterior sampling.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Unsu- pervised anomaly detection via masked diffusion posterior sampling

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.439011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.200448Z digest=sha256:33db2ecf173451861773c70b386a865be1cfae29b0199ff3582c7f74e72b7d5c

Observation 56c16a00-d512-478e-acc5-cd968e913095 · outbound

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

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Defect spectrum: a granular look of large-scale de- fect datasets with rich semantics

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.423671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.204390Z digest=sha256:857ccff1c327e77cf9faff6f2ec57ced483abdf9b2563e1650c0d7c65b516a59

Observation 86b0b182-3cd1-4c91-b00c-84984ca34c62 · outbound

This paper cites Lifelong Learning with Dynamically Expandable Networks.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Lifelong Learning with Dynamically Expandable Networks

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-15T22:42:38.216064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:42:38.216064Z digest=sha256:0fbc41f15a157ee895818c5420c9acc203f336aaad913ab27d190b83cb1233cd

Observation 400511ab-cc32-4ed3-9d87-24e0f33cb55b · outbound

This paper cites A unified model for multi-class anomaly detection.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection A unified model for multi-class anomaly detection

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.409321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.221664Z digest=sha256:98b437deac18492925cb588db614844f06f8051786c12d7ed498f19e55f16b27

Observation 07a74a90-80be-440e-b2f7-69773fc3ddd1 · outbound

This paper cites Learning Feature Inversion for Multi-class Anomaly Detection under General-purpose COCO-AD Benchmark.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Learning Feature Inversion for Multi-class Anomaly Detection under General-purpose COCO-AD Benchmark

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T22:42:38.232373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:42:38.232373Z digest=sha256:ac5668a0e77aebd4f8ce3ec42c444e25a6ca2f12e68a5a8e314877a9f9610b1f

Observation b902ef8a-1363-48f2-9fbb-192dcb1e64a7 · outbound

This paper cites Anomaly detection with robust deep autoen- coders.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Anomaly detection with robust deep autoen- coders

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.392261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.236364Z digest=sha256:0ba7943d76d1ac838131c2f478247ab3a89f92032983babe22588f8c481e759f

Observation 613b0c06-4d26-4adc-b7e9-5850c529da5e · outbound

This paper cites Spot-the-difference self-supervised pre-training for anomaly detection and segmentation.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Spot-the-difference self-supervised pre-training for anomaly detection and segmentation

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.375236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.240181Z digest=sha256:198755220132702a621a3a08836e0a8eb1f77af727860bb01242231c97b0181e

Observation 01664b5e-4755-4e6b-a409-6a74bef66aae · outbound

This paper cites Clip-fsac: Boosting clip for few-shot anomaly classifica- tion with synthetic anomalies.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Clip-fsac: Boosting clip for few-shot anomaly classifica- tion with synthetic anomalies

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.356929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.243873Z digest=sha256:f3158e99621396f5e1df1607e1fde05328ed744e235dc579330dee3fbf9263f5

Observation dad14b52-ca62-4396-b8ad-f990a9fb3158 · outbound

This paper cites As shown in Figure 8, the results below show that ReplayCAD can ef- fectively generate data even when there are significant differ- ences from the pretraining domain.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection As shown in Figure 8, the results below show that ReplayCAD can ef- fectively generate data even when there are significant differ- ences from the pretraining domain

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.343064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.248718Z digest=sha256:b4accef4bb74f3499242cf5664eadac1a1c400279a8a6e0efc39be4c9b85a235

Observation b08bed65-df77-455e-b6a9-40e559dc1d47 · outbound

This paper cites Cutpaste: Self-supervised learn- ing for anomaly detection and localization.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Cutpaste: Self-supervised learn- ing for anomaly detection and localization

Reference 2017

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.662770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.102087Z digest=sha256:becc418202acf8a74ef4c3ee4e52816866f0a2beef8360c44b778e83e3b3dd51

Observation 3f287518-3b94-457a-b9f4-c5b81428491b · outbound

This paper cites The medical segmentation decathlon.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection The medical segmentation decathlon

Reference 2018

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.819421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.019000Z digest=sha256:45f291fa6979fb949fc3bcbac3adae2f0ae736c123bdc1a696afb4779f75d5c3

Observation 0b75edfe-7434-48ff-bb6f-9545674343cc · outbound

This paper cites Rie- mannian walk for incremental learning: Understanding forgetting and intransigence.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Rie- mannian walk for incremental learning: Understanding forgetting and intransigence

Reference 2019

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.793522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.030436Z digest=sha256:274befcff4c2755ba6e25de01dafc0b2bcb6905d033a65f0bbfc7ba8644d5e5f

Observation 8633bbaa-6d88-4440-be21-3f1090eeaffb · outbound

This paper cites Simplenet: A simple network for im- age anomaly detection and localization.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Simplenet: A simple network for im- age anomaly detection and localization

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.601108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.128952Z digest=sha256:3cc8061695ae416e2c05cab909c1b9653566563cd27a57b622daeec0cd0e86c9

Observation a1d313e8-c22d-4981-9905-5a5f0431db3d · outbound

This paper cites Towards continual adaptation in industrial anomaly detection.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Towards continual adaptation in industrial anomaly detection

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.651782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.107215Z digest=sha256:bd39fb4eaf3641c969f208dd32d3f168a5e5270e66520c324dbea0dbf3e55247

Observation f7f5a2da-deb8-408e-8cad-457d4d3d30f1 · outbound

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

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Mvtec ad–a com- prehensive real-world dataset for unsupervised anomaly detection

Reference 2022

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.805709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.025139Z digest=sha256:7d4669fe37df7bbbda6f2fb4a30c273109428ef64938ac61dd2f2b2b0c9da9b4

Observation 5249b092-6701-4348-a257-7ca06d28750a · outbound

This paper cites One-dm: One- shot diffusion mimicker for handwritten text generation.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection One-dm: One- shot diffusion mimicker for handwritten text generation

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.767841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.039337Z digest=sha256:8dee21cf12cfc302136b46a12d7d302247b68d64de1a73f0b66bc2fdfb4e257a

Observation 50d75d42-7834-4423-99ca-f349eef120e7 · outbound

This paper cites Anomaly detection via reverse distillation from one-class embed- ding.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection Anomaly detection via reverse distillation from one-class embed- ding

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.754703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.044485Z digest=sha256:fb05746d41e9c9a5879b72e21844b45c1b215429fb65b3b9e12b8eab9fc8e3be

Observation c7aea44e-1738-45e6-bfe9-f4310562b1ba · outbound

This paper cites The kits21 challenge: Automatic segmentation of kidneys, renal tu- mors, and renal cysts in corticomedullary-phase ct,.

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection The kits21 challenge: Automatic segmentation of kidneys, renal tu- mors, and renal cysts in corticomedullary-phase ct,

Reference 2025

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:38.719219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:42:38.065223Z digest=sha256:116c3f659ed71c74aca4160580ab34b45173fcf265103e6ea1750fe661209c1a

Pith citing papers

Observation f26a431a-f689-4f7a-9ddb-b5d06810b537 · inbound

C3D-AD: Toward Continual 3D Anomaly Detection via Kernel Attention with Learnable Advisor cites this paper.

C3D-AD: Toward Continual 3D Anomaly Detection via Kernel Attention with Learnable Advisor ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T05:47:37.258947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:47:37.258947Z digest=sha256:7f928fc19250d3ffae35b0093d2983e6f1c17251cb1da0fc7d21527bb5563e32

Observation f5c8729a-c9e8-4012-aaf5-549cb9884659 · inbound

Normality-Preserving Continual Industrial Anomaly Detection via Orthogonal LoRA Banks cites this paper.

Normality-Preserving Continual Industrial Anomaly Detection via Orthogonal LoRA Banks ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-07-01T22:16:15.686477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-28T15:39:42.265865Z digest=sha256:b00a356dd493f4fb6fefbea0b95f5904ccedfd471c291552c94209222e3ffb86

Observation 86de6881-7cf7-4ee5-a36f-056cf8115f8b · inbound

DeCoFlow: Structural Decomposition of Normalizing Flows for Continual Anomaly Detection cites this paper.

DeCoFlow: Structural Decomposition of Normalizing Flows for Continual Anomaly Detection ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-04T12:49:52.972450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-26T05:48:58.268345Z digest=sha256:c5635529e90a4349e41cdeb0d7e6ce49ebcb2e2d5f5475f71c55ff1d416f60f3

Observation 2e8b1cdb-5824-4555-8ea4-7a36e08bf2b4 · inbound

DeCoFlow: Structural Decomposition of Normalizing Flows for Continual Anomaly Detection cites this paper.

DeCoFlow: Structural Decomposition of Normalizing Flows for Continual Anomaly Detection ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection

Reference 10

Resolution
unresolved
no resolver link, observed 2026-07-12T11:56:43.996418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T11:56:43.996418Z digest=sha256:228107f0000eb1c5ac492f87579ed79d84cdc34c7345f64a35dcb229b33ea490

Observation 260feff0-0ba7-4d62-9df6-1cfdb2ece4d9 · inbound

Towards Principled Continual Anomaly Detection: A Systematic Framework and Benchmark Scenarios cites this paper.

Towards Principled Continual Anomaly Detection: A Systematic Framework and Benchmark Scenarios ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-02T09:22:42.372529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T09:22:42.372529Z digest=sha256:62303f9aef152ad56ac8b7bcf2ae13f8e0e9b09bfd370475f6118f1739641e2f