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Paper Citation Record · LEDGER

A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2401.16402.

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

pith.paper-citation-record.v1
2401.16402 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:57:04.556285Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

9
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3c02bd78-f604-42d4-b6e8-301cbf2e96cd · inbound

ROADS: Robust Prompt-driven Multi-Class Anomaly Detection under Domain Shift cites this paper.

ROADS: Robust Prompt-driven Multi-Class Anomaly Detection under Domain Shift A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 4

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no resolver link, observed 2026-08-12T13:39:38.543325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:39:38.543325Z digest=sha256:f427318065501f231eb2e0418722ec4852f2dfd1749ea4f6cb410100ebe33ab3

Observation 25100388-7f90-4add-bbb5-f23867fb6122 · inbound

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties cites this paper.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 8

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no resolver link, observed 2026-08-11T12:07:51.236255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:07:51.236255Z digest=sha256:68256fa47f147734dbcd965720528729c391f66ca224b4bb47b55cd3fe2a6daf

Observation b1e9870d-f13c-4876-ae3c-b5949295a663 · inbound

Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection? cites this paper.

Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection? A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 3

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unresolved
no resolver link, observed 2026-08-10T14:03:30.950201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:03:30.950201Z digest=sha256:922149bc73227fc9e749076f69bab775b31b45881daae31542613950290515fb

Observation 13feb1b7-5809-4631-8256-723e7e6aea04 · inbound

3CAD: A Large-Scale Real-World 3C Product Dataset for Unsupervised Anomaly cites this paper.

3CAD: A Large-Scale Real-World 3C Product Dataset for Unsupervised Anomaly A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 5

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no resolver link, observed 2026-08-08T18:08:02.581927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T18:08:02.581927Z digest=sha256:a1660dae7e4cda7b881ec846a05d7ee461dc7623fa05ee1a2daaf3dae0b3fd5b

Observation 52238573-fb9e-4ff6-8686-4a4b1561f796 · inbound

Real-IAD D3: A Real-World 2D/Pseudo-3D/3D Dataset for Industrial Anomaly Detection cites this paper.

Real-IAD D3: A Real-World 2D/Pseudo-3D/3D Dataset for Industrial Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 6

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unresolved
no resolver link, observed 2026-08-16T11:57:04.556285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:57:04.556285Z digest=sha256:de50ed21af9a42d7fdd380b7b60280b910d727893af6a8b3766a7f1c6f789f99

Observation bfc705f3-9a44-40b2-a0f7-21b20f850b2c · inbound

RoBiS: Robust Binary Segmentation for High-Resolution Industrial Images cites this paper.

RoBiS: Robust Binary Segmentation for High-Resolution Industrial Images A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 4

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unresolved
no resolver link, observed 2026-08-07T13:43:19.564441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:43:19.564441Z digest=sha256:e5bce08c0650b2e218052f1632baea9443d4c0d70fc5718285c95415d28c3e1f

Observation 0d8d4d6b-ef16-4a97-8ae1-00b0847a108b · inbound

INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual Learning cites this paper.

INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual Learning A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 3

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unresolved
no resolver link, observed 2026-08-07T11:03:10.179143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:10.179143Z digest=sha256:0c766c4fb2f5028a2562e6cccceed5b3073a2deaa5ca9c603cf39df07af6f391

Observation 6e4df65f-c3a3-4497-90c1-a70de2bb8739 · inbound

IQE-CLIP: Instance-aware Query Embedding for Zero-/Few-shot Anomaly Detection in Medical Domain cites this paper.

IQE-CLIP: Instance-aware Query Embedding for Zero-/Few-shot Anomaly Detection in Medical Domain A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 12

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no resolver link, observed 2026-08-07T04:28:33.889507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:28:33.889507Z digest=sha256:5cb2e8307426a941bc5056c2ccefd16be2536a015728f034178ec414ce4454a2

Observation fb3c09f8-c92a-4682-9b20-820db08f938d · inbound

Quantitative Benchmarking of Anomaly Detection Methods in Digital Pathology cites this paper.

Quantitative Benchmarking of Anomaly Detection Methods in Digital Pathology A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 7

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no resolver link, observed 2026-08-06T23:10:07.273869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:07.273869Z digest=sha256:4cbca14b948e5455bb5e1f5f8cc4069061d3d3b44644d5bc4240c61f5b2fbeb2

Observation b1e08200-9070-44a0-9221-a2fc00ca7fe4 · inbound

Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection cites this paper.

Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 6

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no resolver link, observed 2026-08-06T17:27:14.370852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:27:14.370852Z digest=sha256:270c30016ddb57ce8c7d9415593550ef7ccc3ec59ff0eb31d7078a88c95d82b3

Observation 0586d6c5-16c4-4d0e-b566-d98a2546d706 · inbound

A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects cites this paper.

A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 3

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unresolved
no resolver link, observed 2026-08-06T17:21:37.814140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:21:37.814140Z digest=sha256:80f309cc5a263a177edec0f4bb39ab4c361935ff11cdac9622735fdde93d1ff8

Observation 451ac339-7fed-44e0-b369-95bb97edd32f · inbound

Toward Long-Tailed Online Anomaly Detection through Class-Agnostic Concepts cites this paper.

Toward Long-Tailed Online Anomaly Detection through Class-Agnostic Concepts A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 8

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unresolved
no resolver link, observed 2026-08-06T15:06:24.391064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:06:24.391064Z digest=sha256:33c7515472049ebb5175a036ecf09c991e742e3b357bbd649d493976251c2b36

Observation 850c0368-daaf-4000-8600-65c757fd7985 · inbound

MCL-AD: Multimodal Collaboration Learning for Zero-Shot 3D Anomaly Detection cites this paper.

MCL-AD: Multimodal Collaboration Learning for Zero-Shot 3D Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 18

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unresolved
no resolver link, observed 2026-08-15T15:59:52.510832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:59:52.510832Z digest=sha256:7068397f88f9832d024b966618ae6e7db73dad2ddccf25e0da6f1d68df986007

Observation 4031733d-72e8-47bf-8187-2146473587c1 · inbound

Normality Calibration in Semi-supervised Graph Anomaly Detection cites this paper.

Normality Calibration in Semi-supervised Graph Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 1

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unresolved
no resolver link, observed 2026-08-04T12:48:07.552118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:48:07.552118Z digest=sha256:de22adabfafe03a7e1f16193b5d2940131fcf16c25ed31425cfe97ed5bb6935f

Observation 7c4ae927-032b-43a3-b996-0ed92a823508 · inbound

SGANet: Semantic and Geometric Alignment for Multimodal Multi-view Anomaly Detection cites this paper.

SGANet: Semantic and Geometric Alignment for Multimodal Multi-view Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:05:48.336594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-10T20:16:06.916465Z digest=sha256:36cf8f3418ec3ecdb9279f3a6a1e0506b6e4be526210cbf477e71e19fc01433b

Observation 0ba0a0f9-19aa-4d8c-845e-e5684879f3b7 · inbound

GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis cites this paper.

GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 2

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verified exact
arxiv_id, observed 2026-05-11T00:35:49.404243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-10T18:27:36.529298Z digest=sha256:2bc24262931d13894418e0ae558438ef724d5736d2a7664aeb3c954ef2c8bd98

Observation 424e1e87-4438-42b0-a255-3b4132df0fb8 · inbound

Beyond Normal References: Discriminative Few-Shot Anomaly Detection cites this paper.

Beyond Normal References: Discriminative Few-Shot Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 2

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verified exact
arxiv_id, observed 2026-05-25T04:55:23.664104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-25T04:52:07.114651Z digest=sha256:b5c7edca64ec771b9cea2a8d0c5dba0744409bdaf5f089a9f7cf4c20c77fc4bf

Observation 119bd49d-f4b8-4254-b0a9-56362bd330ec · inbound

Dual Prototype-Conditioned Diffusion Model for Scalable Multi-Class Unsupervised Anomaly Detection in Large Category Spaces cites this paper.

Dual Prototype-Conditioned Diffusion Model for Scalable Multi-Class Unsupervised Anomaly Detection in Large Category Spaces A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 4

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verified exact
arxiv_id, observed 2026-06-30T13:54:44.040833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-30T13:48:39.954133Z digest=sha256:ee247386e363c352477200d14f9a423c45498cc9b6abf1d1ea586ef2a591446c

Observation 0f7edb27-980b-461c-bf01-b4aa0f51d615 · inbound

AnomalyAgent: Training-Free Agentic Models for Zero-/Few-Shot Anomaly Detection cites this paper.

AnomalyAgent: Training-Free Agentic Models for Zero-/Few-Shot Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 4

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verified exact
arxiv_id, observed 2026-06-29T08:13:14.940540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-29T08:10:15.306343Z digest=sha256:217cdd7b3d3868718b9d746bbe5009ebdcec6d13b40fcad1dcae8371e754a45e

Observation 536d2f97-8c91-4749-9a1a-943838807657 · inbound

HiMatch-AD: DINOv3-driven Hierarchical Matching for Training-free Medical Anomaly Detection cites this paper.

HiMatch-AD: DINOv3-driven Hierarchical Matching for Training-free Medical Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 7

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verified exact
arxiv_id, observed 2026-07-04T08:39:42.031321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-26T11:16:57.088304Z digest=sha256:ae233b75f7b6c5488b8cfb35a7a7446f6fb3394f1df2810f02b751ebda875dab

Observation cd9c8230-8b66-4159-894f-d9a31908934f · inbound

MambaADv2: Evolving Duality-enhanced State Space Model for Unsupervised Anomaly Detection cites this paper.

MambaADv2: Evolving Duality-enhanced State Space Model for Unsupervised Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 16

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metadata mismatch
arxiv_id, observed 2026-07-04T09:49:44.646264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-26T09:26:51.456652Z digest=sha256:80ad7f87ab010dd8bb120a85b900f078e7d44e36b7f50fadd69554a44f4f5a45

Observation 4d9bc430-1345-4a97-8376-0cedb2278b18 · inbound

CoGeoAD: Hierarchical Color-Geometric Fusion with Multi-View Attention for Zero-Shot 3D Anomaly Detection cites this paper.

CoGeoAD: Hierarchical Color-Geometric Fusion with Multi-View Attention for Zero-Shot 3D Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 7

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verified exact
arxiv_id, observed 2026-07-04T19:50:10.591635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-06-25T20:59:46.355482Z digest=sha256:04df2cb15196e79ee6e6434a61c3b98d3fccb70b563833d740f26c5fbac2a381

Observation 25a0d44a-ee7b-4dd9-ad76-66f1b891629d · 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 A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 4

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metadata mismatch
arxiv_id, observed 2026-07-01T17:15:50.964359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-29T04:05:22.253489Z digest=sha256:fbace41cfbb49b5652bb0a1575d099884e130b6e2b1b20fcafe8421738c8d50d

Observation ad0b0165-bd65-4a8d-8b50-dffdbf8e57d2 · inbound

Anomaly Factory 3D: A Modular Framework for Diverse Pseudo-Anomaly Synthesis in Unsupervised 3D Anomaly Detection cites this paper.

Anomaly Factory 3D: A Modular Framework for Diverse Pseudo-Anomaly Synthesis in Unsupervised 3D Anomaly Detection A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 3

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verified exact
arxiv_id, observed 2026-06-30T07:54:21.172788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-30T07:53:44.196356Z digest=sha256:c915ae3632b44ede7fd7bb1809b9b47d24401c73c3b5ad1eb3727729ddf16d07

Observation 4297816f-9c2f-49b2-bbc4-68473cd4ae7e · inbound

Robust Zero-shot Anomaly Detection under Limited Auxiliary Anomaly Priors cites this paper.

Robust Zero-shot Anomaly Detection under Limited Auxiliary Anomaly Priors A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 5

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verified exact
arxiv_id, observed 2026-06-30T07:54:21.686229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-30T07:54:02.833347Z digest=sha256:74d63efec0e0dbe52c21862bd83a913c3406b31fc0e1b622252b0944fda5c785