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Paper Citation Record · LEDGER

Towards Continual Visual Anomaly Detection in the Medical Domain

As of 17 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2508.18013.

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

pith.paper-citation-record.v1
2508.18013 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:39:46.252583Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

24 of 24 outbound references displayed

  • verified exact2
  • verified fuzzy20
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 79919488-fc80-404f-9fdd-db0559abab98 · outbound

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

Towards Continual Visual Anomaly Detection in the Medical Domain Mvtec ad — a comprehensive real-world dataset for unsupervised anomaly detection

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.953311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.025870Z digest=sha256:de00966431c6f2ce9c82ccaf734234cba4c563d875952eadc21ef7289918c2b7

Observation fee5074c-0fee-47d4-9805-5f9f448b08a5 · outbound

This paper cites an unresolved cited work.

Towards Continual Visual Anomaly Detection in the Medical Domain Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:39:46.931362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.032948Z digest=sha256:9176f52c5e1b92a9ff17d1594308c4d30441f2b65702ba1f2955333c53e317dd

Observation 2ffc304f-7dd4-4dfd-bb52-174d65b449d0 · outbound

This paper cites BMAD: Benchmarks for Medical Anomaly Detection.

Towards Continual Visual Anomaly Detection in the Medical Domain BMAD: Benchmarks for Medical Anomaly Detection

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-08-05T16:39:46.413583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.047998Z digest=sha256:bf7cc42258c94ca2e7f7c0f6bef31abb43fb0a514151f1c1087c123d543d70db

Observation bb959c59-7b4c-4ab4-9d0e-2f91b80d533b · outbound

This paper cites Towards total recall in industrial anomaly detection.

Towards Continual Visual Anomaly Detection in the Medical Domain Towards total recall in industrial anomaly detection

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.905634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.069685Z digest=sha256:8fff8a8b33eeec5c37f20a1d85e4d5e8bb67ecc02e2da334d8900c6efc6d5f8b

Observation 2dfe7e2b-d4f1-4523-adea-c310eb104515 · outbound

This paper cites Unveiling the anomalies in an ever-changing world: A benchmark for pixel-level anomaly detection in continual learning.

Towards Continual Visual Anomaly Detection in the Medical Domain Unveiling the anomalies in an ever-changing world: A benchmark for pixel-level anomaly detection in continual learning

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.885323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.083235Z digest=sha256:99714826a69ee0ba1ace24ce3a2f53c1b223d7a9fa8db0e2c3ccfd9bcf520fde

Observation 69187bd8-deae-4577-8cef-75377b75cb5e · outbound

This paper cites Moviad: A modular library for visual anomaly detection, 2025.

Towards Continual Visual Anomaly Detection in the Medical Domain Moviad: A modular library for visual anomaly detection, 2025

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.860277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.105159Z digest=sha256:52f13c94ee13810466d16d759b928406a8f8430b2f5b241ca9088fd398763235

Observation d98868ea-e539-4fee-aaf1-6a3ade78899c · outbound

This paper cites Draem -- a discriminatively trained reconstruction embedding for surface anomaly detection, 2021.

Towards Continual Visual Anomaly Detection in the Medical Domain Draem -- a discriminatively trained reconstruction embedding for surface anomaly detection, 2021

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.827911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.112231Z digest=sha256:4b934ebb7149182cc31be7aa0984161843c213c5420d351588b48a4eeea8d595

Observation df89a081-df5a-435d-ad45-045c35079125 · outbound

This paper cites Reconstruction by inpainting for visual anomaly detection.

Towards Continual Visual Anomaly Detection in the Medical Domain Reconstruction by inpainting for visual anomaly detection

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.806360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.118166Z digest=sha256:56fdbda1d5bdbfa2cc1be7a7d681d066676ce8353a764613506f2ceaf8eb0a5d

Observation 661c8bee-cc5e-4290-ba33-cab4a68b11f4 · outbound

This paper cites Paste: Improving the efficiency of visual anomaly detection at the edge.

Towards Continual Visual Anomaly Detection in the Medical Domain Paste: Improving the efficiency of visual anomaly detection at the edge

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.780261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.124521Z digest=sha256:b39d847b3c0754423c477af2b02ceabac11d6c4b96532f5c472fdc4d4ca44e24

Observation 87dc01b6-3e7a-4dfd-ba5d-a5e5287445e1 · outbound

This paper cites Memory efficient continual learning for edge-based visual anomaly detection, 2025.

Towards Continual Visual Anomaly Detection in the Medical Domain Memory efficient continual learning for edge-based visual anomaly detection, 2025

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.756528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.132665Z digest=sha256:34501c0f4290fd409235286512045d8fbc54f1f3a9b8f8108d9bf01f5b88d058

Observation 3dac69da-0f5d-4b56-bb34-66ce18505260 · outbound

This paper cites Experience replay for continual learning.

Towards Continual Visual Anomaly Detection in the Medical Domain Experience replay for continual learning

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.733238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.137901Z digest=sha256:08930f4f13ca5c3166986afa036d8d702948f5e124c9ee0e15cf8da1694350f4

Observation 9f30cb42-f27d-4696-bb93-52a86802dba9 · outbound

This paper cites Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell.

Towards Continual Visual Anomaly Detection in the Medical Domain Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.714400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.144999Z digest=sha256:906a46cd3fe752e9178d733910f6aae80703c615a2d45f69fabce402fb4d44b2

Observation e79dc011-fe60-4dcd-a14f-9e2af661805d · outbound

This paper cites Learning without forgetting, 2017.

Towards Continual Visual Anomaly Detection in the Medical Domain Learning without forgetting, 2017

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.695252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.164511Z digest=sha256:a636a0d9cbdf6e453a9d5980fce23eaf038091e5751cb3695459cec74bafa123

Observation 55e5fb99-4ec8-46a3-8904-04cf6523bbc2 · outbound

This paper cites Rusu, Alexander Pritzel, and Daan Wierstra.

Towards Continual Visual Anomaly Detection in the Medical Domain Rusu, Alexander Pritzel, and Daan Wierstra

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.675713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.171948Z digest=sha256:9808595814ab2d31ca32979fe23d7491b942cb8071fc8e2d137fb6992227fb70

Observation 7e2e96ff-8fd1-40b2-afa8-b8437d7c62e3 · outbound

This paper cites Packnet: Adding multiple tasks to a single network by iterative pruning, 2018.

Towards Continual Visual Anomaly Detection in the Medical Domain Packnet: Adding multiple tasks to a single network by iterative pruning, 2018

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.648965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.179853Z digest=sha256:17817e54959554faa2b4b4416b89c17afc3d6d8c187aab24e90b13fd47e394d7

Observation ef95b3c6-c107-4381-a525-aa1f4cf310d5 · outbound

This paper cites Latent replay for real-time continual learning, 2020.

Towards Continual Visual Anomaly Detection in the Medical Domain Latent replay for real-time continual learning, 2020

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.614453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.187190Z digest=sha256:254c2d129bad70e0df64fda2f46d33a72a555231d5ac2f280dc3db5f5214c4fa

Observation 2d3c00cc-1bac-4ddc-a8ab-052367cbae23 · outbound

This paper cites Learn to detect objects incrementally.

Towards Continual Visual Anomaly Detection in the Medical Domain Learn to detect objects incrementally

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.583810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.198178Z digest=sha256:9dc308485b98517d34ec6392b10491a4a969dc3fa451396b5635536cce3c11b4

Observation 575062d8-7f6b-40ca-9ca6-2877e208cdf2 · outbound

This paper cites Towards continual adaptation in industrial anomaly detection.

Towards Continual Visual Anomaly Detection in the Medical Domain Towards continual adaptation in industrial anomaly detection

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.555574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.204422Z digest=sha256:9bd282d175e252ef48ff700c4369b81cda4d13466d868d7b2d5504f0444c0d5c

Observation e8335c78-6263-4ca8-883c-ddb2948addf4 · outbound

This paper cites Continual Learning Approaches for Anomaly Detection.

Towards Continual Visual Anomaly Detection in the Medical Domain Continual Learning Approaches for Anomaly Detection

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-05T16:39:46.373398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.210457Z digest=sha256:de07e2e81c492cd373936baf1d758f95a0cd2df63d2786ca98fb9ce6cf3974af

Observation cc486d5a-01c3-40b6-b10e-13889b09fa7a · outbound

This paper cites Student-Teacher Feature Pyramid Matching for Anomaly Detection.

Towards Continual Visual Anomaly Detection in the Medical Domain Student-Teacher Feature Pyramid Matching for Anomaly Detection

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-05T16:39:46.216657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:39:46.216657Z digest=sha256:5285ca701c63017984562b9bf5056e10ec5fee6fb32a7cfbc77eca3c7f0fb42b

Observation 70f29f72-0959-4998-ad33-7d9467f91786 · outbound

This paper cites Efficientad: Accurate visual anomaly detection at millisecond-level latencies, 2024.

Towards Continual Visual Anomaly Detection in the Medical Domain Efficientad: Accurate visual anomaly detection at millisecond-level latencies, 2024

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.525606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.232368Z digest=sha256:7f124f75cd4e2c250b1d7b6c024e72cda163548a89da1d1b4d93338b3578401b

Observation b68fa004-2a1f-4d4b-b104-c586976cabe5 · outbound

This paper cites Fastflow: Unsupervised anomaly detection and localization via 2d normalizing flows, 2021.

Towards Continual Visual Anomaly Detection in the Medical Domain Fastflow: Unsupervised anomaly detection and localization via 2d normalizing flows, 2021

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.497636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.237915Z digest=sha256:05b7baa6d0f8bc1cae18015b6ec6a72e7df3af4629e2668c0228596d32dc6da5

Observation 3a2e26c2-9a54-419c-934a-d6a892b1e649 · outbound

This paper cites Unsupervised continual anomaly detection with contrastively-learned prompt.

Towards Continual Visual Anomaly Detection in the Medical Domain Unsupervised continual anomaly detection with contrastively-learned prompt

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.470705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.244896Z digest=sha256:aa9be956bd77f26b91a207e1d6a0ec483cb33ae4e6b96fc009e0b2fe9269f527

Observation 6b409ee3-f22a-4770-a48e-39b50d65d057 · outbound

This paper cites Wide residual networks, 2017.

Towards Continual Visual Anomaly Detection in the Medical Domain Wide residual networks, 2017

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:39:46.448015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:39:46.252583Z digest=sha256:d571bdee318a01edbb361e5587d440db8f2ad0711eea1de4a5ff662ed5dab67a

Pith citing papers

No inbound Pith citation observations are available.