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Paper Citation Record · LEDGER

SALAD -- Semantics-Aware Logical Anomaly Detection

As of 20 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2509.02101.

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

pith.paper-citation-record.v1
2509.02101 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:56:37.520732Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

47 of 47 outbound references displayed

  • verified exact0
  • verified fuzzy42
  • unresolved4
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 411cbc62-4907-42c0-9d3c-7bf8b5a7d45b · outbound

This paper cites Efficien- tAD: Accurate Visual Anomaly Detection at Millisecond- Level Latencies.

SALAD -- Semantics-Aware Logical Anomaly Detection Efficien- tAD: Accurate Visual Anomaly Detection at Millisecond- Level Latencies

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.283396Z digest=sha256:e46ac6ca6de11a298f35741f552c393458429d94d266dbacf3504a6fc225ab6d

Observation b0664723-8f5f-410d-ac3c-ae6df63e2623 · outbound

This paper cites The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsuper- vised Anomaly Detection.

SALAD -- Semantics-Aware Logical Anomaly Detection The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsuper- vised Anomaly Detection

Reference 2

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raw_fallback, observed 2026-08-05T11:56:38.411929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.288697Z digest=sha256:ad34b14db955624a15128008f8b0f6ae9adc2af7633de98e9f97b2e24c9c81ce

Observation e8277ac3-4691-4cba-aca8-a9172b80bc25 · outbound

This paper cites Beyond Dents and Scratches: Logical Constraints in Unsupervised Anomaly Detection and Localization.

SALAD -- Semantics-Aware Logical Anomaly Detection Beyond Dents and Scratches: Logical Constraints in Unsupervised Anomaly Detection and Localization

Reference 3

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raw_fallback, observed 2026-08-05T11:56:38.395708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.293594Z digest=sha256:27d3f6ef481bf3a7b6d267dd7520b87d7ba11168f06d0e4e849be727362d21ed

Observation 195bde26-e0c7-4fd4-8b6c-465a558578f4 · outbound

This paper cites Mixed supervision for surface-defect detection: From weakly to fully supervised learning.

SALAD -- Semantics-Aware Logical Anomaly Detection Mixed supervision for surface-defect detection: From weakly to fully supervised learning

Reference 4

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raw_fallback, observed 2026-08-05T11:56:38.377671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.298401Z digest=sha256:e780e7e97e69d348868bf22261759c91ca5e239c9974f4c77582ecfd555cdc72

Observation 58521328-df35-4367-9d7f-ad0b60b92756 · outbound

This paper cites Robustness of unsupervised methods for image surface-anomaly detection.

SALAD -- Semantics-Aware Logical Anomaly Detection Robustness of unsupervised methods for image surface-anomaly detection

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.304560Z digest=sha256:b2997298b52c9d3f7713aad557b862af61f2529001c5976ca3efe9eb55795a24

Observation 2a2a41e8-b914-4e50-8345-c6a490efab74 · outbound

This paper cites Emerg- ing properties in self-supervised vision transformers.

SALAD -- Semantics-Aware Logical Anomaly Detection Emerg- ing properties in self-supervised vision transformers

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.309669Z digest=sha256:6918242a84ab5cda89c1167fe800d39ffcdd5f25a80f5ce07b2a63a1954445b7

Observation be1e3841-7520-4caa-b4ed-a3fbc15a5a0c · outbound

This paper cites Set Features for Anomaly Detection.

SALAD -- Semantics-Aware Logical Anomaly Detection Set Features for Anomaly Detection

Reference 7

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unresolved
no resolver link, observed 2026-08-05T11:56:37.315774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:56:37.315774Z digest=sha256:38b568eb1035f65c16a9959271381b2e87d9e078788cd1947f3b644cd2a8f7e4

Observation 09d6f15a-4ed6-448e-8114-f07ea762d617 · outbound

This paper cites Generating and reweighting dense contrastive patterns for unsupervised anomaly detection.

SALAD -- Semantics-Aware Logical Anomaly Detection Generating and reweighting dense contrastive patterns for unsupervised anomaly detection

Reference 8

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raw_fallback, observed 2026-08-05T11:56:38.316843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.320490Z digest=sha256:6acda3c4820f06d69387469e35d50b47e960dc3f3cd49be547baee18f8c15035

Observation fd056d53-82e6-4f4c-a3ba-1c2d9d817d6f · outbound

This paper cites Anomaly Detection via Reverse Distillation From One-Class Embedding.

SALAD -- Semantics-Aware Logical Anomaly Detection Anomaly Detection via Reverse Distillation From One-Class Embedding

Reference 9

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raw_fallback, observed 2026-08-05T11:56:38.293604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.325476Z digest=sha256:9501700e34c27923f022d5a83f72cdb6033b23924916b63213dc3051c928ec2e

Observation 83483ce3-2a93-46de-b67b-3e744093dc81 · outbound

This paper cites ImageNet: A large-scale hierarchical image database.

SALAD -- Semantics-Aware Logical Anomaly Detection ImageNet: A large-scale hierarchical image database

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.330333Z digest=sha256:136ec13e724df7dc28d6d5388390a030b641387b6c861f52a787a09f53004e04

Observation 068e4afd-ead1-4543-866d-17d70b67eb26 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

SALAD -- Semantics-Aware Logical Anomaly Detection An image is worth 16x16 words: Transformers for image recognition at scale

Reference 11

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raw_fallback, observed 2026-08-05T11:56:38.256622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.335394Z digest=sha256:000e1d7a11997755e1856a28fcab15d9dc1d4e4478f55d3cddecac5a0d878a1f

Observation 04c59607-e5a3-4d2f-bf9a-924bcd2938bf · outbound

This paper cites TransFu- sion – A Transparency-Based Diffusion Model for Anomaly Detection.

SALAD -- Semantics-Aware Logical Anomaly Detection TransFu- sion – A Transparency-Based Diffusion Model for Anomaly Detection

Reference 12

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raw_fallback, observed 2026-08-05T11:56:38.236587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.339607Z digest=sha256:bbd4449def594ee2decebd8b177bfaa718ee71f7335da48ac199e42e741d1328

Observation b54e8dda-490b-4615-8ed0-b973268005e7 · outbound

This paper cites CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows.

SALAD -- Semantics-Aware Logical Anomaly Detection CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows

Reference 13

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raw_fallback, observed 2026-08-05T11:56:38.217195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.344480Z digest=sha256:accf5c86eb5ada202cf03e0fbdf0e82b2ae7507af160688109ab918f7ad97311

Observation 2aa44133-5426-4e6e-820b-3d24aad73899 · outbound

This paper cites Template-guided hierarchical feature restoration for anomaly detection.

SALAD -- Semantics-Aware Logical Anomaly Detection Template-guided hierarchical feature restoration for anomaly detection

Reference 14

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raw_fallback, observed 2026-08-05T11:56:38.197047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.348951Z digest=sha256:044c96463fd2d16e9c15e3912172986e744879ac8cf41f55610f092e20ed4a10

Observation a78b7419-3df9-4c05-9f86-a42dcdb5847d · outbound

This paper cites Deep Residual Learning for Image Recognition.

SALAD -- Semantics-Aware Logical Anomaly Detection Deep Residual Learning for Image Recognition

Reference 15

Resolution
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raw_fallback, observed 2026-08-05T11:56:38.176622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.354195Z digest=sha256:6ceaa6c4e3ca945c0c9c0cc858f46ac6cc9c261f94785c8e519ccf8df1c42603

Observation 297f0aec-47b6-41c4-8380-a8a262d88d6d · outbound

This paper cites CSAD: Unsupervised component segmentation for logical anomaly detection.

SALAD -- Semantics-Aware Logical Anomaly Detection CSAD: Unsupervised component segmentation for logical anomaly detection

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.360391Z digest=sha256:ada372e96d2593d3cdaca2783ef3363c3b59185acb0ef6d4827c1e05d7f40d5a

Observation 39cd23b4-6832-49e7-a1e5-7ee4fe9cf05c · outbound

This paper cites Logi- cAD: Explainable Anomaly Detection via VLM-based Text Feature Extraction.

SALAD -- Semantics-Aware Logical Anomaly Detection Logi- cAD: Explainable Anomaly Detection via VLM-based Text Feature Extraction

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.365226Z digest=sha256:82b682eb71f23d49ba6ee668d36ba823580a1bd243816bb1d24bffc106f2e9a7

Observation 1ae16b54-77d4-4a7a-b34a-a8fbdbdf4a47 · outbound

This paper cites Segment anything in high quality.

SALAD -- Semantics-Aware Logical Anomaly Detection Segment anything in high quality

Reference 18

Resolution
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raw_fallback, observed 2026-08-05T11:56:38.122459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.372120Z digest=sha256:489414aaf6296a56272e5aa80e32a4430474715ded37af32098d77d8fc22ef2d

Observation 434fa0ef-9589-46c1-97f5-8916a6bada61 · outbound

This paper cites Few shot part segmentation reveals compositional logic for industrial anomaly detection.

SALAD -- Semantics-Aware Logical Anomaly Detection Few shot part segmentation reveals compositional logic for industrial anomaly detection

Reference 19

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raw_fallback, observed 2026-08-05T11:56:38.105128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.377425Z digest=sha256:5f5604c702d33c21b6847f19f2f846cf35575e60476f6c9f63aac8db3e364679

Observation 240f712d-22bc-444c-8d22-b741c2b15853 · outbound

This paper cites Kingma and Jimmy Ba.

SALAD -- Semantics-Aware Logical Anomaly Detection Kingma and Jimmy Ba

Reference 20

Resolution
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raw_fallback, observed 2026-08-05T11:56:38.082997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.382709Z digest=sha256:2799011b83301a20a840ae8198d97ce6da9c1566687d3c80755952d0bee3f1d2

Observation 951198c8-6de4-48ef-b29d-819e8bfa7be1 · outbound

This paper cites Omni-Frequency Channel-Selection Representations for Unsupervised Anomaly Detection.

SALAD -- Semantics-Aware Logical Anomaly Detection Omni-Frequency Channel-Selection Representations for Unsupervised Anomaly Detection

Reference 21

Resolution
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raw_fallback, observed 2026-08-05T11:56:38.066676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.386964Z digest=sha256:ba1bbfaee556f83fb24695fb57635203dc4939f6b1a2afe8c18e1f8621376774

Observation 1b7a0718-625b-41cd-9701-1852d57784fa · outbound

This paper cites Focal loss for dense object detection.

SALAD -- Semantics-Aware Logical Anomaly Detection Focal loss for dense object detection

Reference 22

Resolution
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raw_fallback, observed 2026-08-05T11:56:38.051036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.391756Z digest=sha256:513eb5ee375f54ff32563cf51e82336025675d4ce35fc0fe5e1e5ae3a99bc85b

Observation 9b7adf48-8280-4454-bcf6-50220915da5b · outbound

This paper cites FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly Detection.

SALAD -- Semantics-Aware Logical Anomaly Detection FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly Detection

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-05T11:56:37.397405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:56:37.397405Z digest=sha256:d61dc0d6037df7627224801c503c2f28b0d94646e26438c2fd41f7bcd1d60626

Observation ba5ea16f-1f8b-4879-8ad4-b6964501ab2f · outbound

This paper cites Component-aware anomaly detection framework for adjustable and logical industrial visual inspec- tion.

SALAD -- Semantics-Aware Logical Anomaly Detection Component-aware anomaly detection framework for adjustable and logical industrial visual inspec- tion

Reference 24

Resolution
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raw_fallback, observed 2026-08-05T11:56:38.033365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.402634Z digest=sha256:cc92351e63ad56d82462464129842166d565c36b74ed1629cfbcf06be5f51260

Observation f6a95a0a-ca42-4c52-9086-b9078668a32a · outbound

This paper cites SimpleNet: A Simple Network for Image Anomaly Detection and Localization.

SALAD -- Semantics-Aware Logical Anomaly Detection SimpleNet: A Simple Network for Image Anomaly Detection and Localization

Reference 25

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raw_fallback, observed 2026-08-05T11:56:38.016263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.410949Z digest=sha256:63e5a65767e2cae2de7c0fc1f84ef263e5701dfe1e3523c34e093920fac0a551

Observation a1725f26-6639-4323-97eb-f5ada2123817 · outbound

This paper cites Decoupled Weight Decay Regularization.

SALAD -- Semantics-Aware Logical Anomaly Detection Decoupled Weight Decay Regularization

Reference 26

Resolution
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raw_fallback, observed 2026-08-05T11:56:37.997620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.416145Z digest=sha256:340b5847ed9aa9b91fea864342a56a47cbbd68085bb5e7a0d4665ed05a5f7f56

Observation 1ab22179-9d7e-4903-95d3-d3246bbc56a7 · outbound

This paper cites an unresolved cited work.

SALAD -- Semantics-Aware Logical Anomaly Detection Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-05T11:56:37.971039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.420750Z digest=sha256:22a527a6ff331fdf8f5547c4a73e92cefff57347814604f0b6b0fe7ce134f10f

Observation 70c1094d-fe74-4c26-9e5e-1273d89f06cd · outbound

This paper cites SAM-LAD: Segment Anything Model meets zero-shot logic anomaly detection.

SALAD -- Semantics-Aware Logical Anomaly Detection SAM-LAD: Segment Anything Model meets zero-shot logic anomaly detection

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.945982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.426248Z digest=sha256:70b919d253dd46924c892f34d1298d61d83859672f3d25501876188582899c5e

Observation 4519bbdf-ba74-4aef-9d0a-9082c19b45de · outbound

This paper cites An image synthesizer.

SALAD -- Semantics-Aware Logical Anomaly Detection An image synthesizer

Reference 29

Resolution
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raw_fallback, observed 2026-08-05T11:56:37.926715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.430575Z digest=sha256:e059ee96b60bd21abdbd21c9a1168b0802df57273b50c3883a49be6ba541e750

Observation 5099070e-dcc8-49cf-b981-2700dcff7b97 · outbound

This paper cites Inpainting transformer for anomaly detection.

SALAD -- Semantics-Aware Logical Anomaly Detection Inpainting transformer for anomaly detection

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.911886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.435365Z digest=sha256:cb9aad52261f06ba7b5605c6c71110df46ad253d9db09f294f8fc43f0f48d847

Observation bc9de1a5-1b89-4182-9294-0bca75fab566 · outbound

This paper cites Modeling the distribution of normal data in pre-trained deep features for anomaly detection.

SALAD -- Semantics-Aware Logical Anomaly Detection Modeling the distribution of normal data in pre-trained deep features for anomaly detection

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.891879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.439534Z digest=sha256:ed307b9ac354da50117c57846147ae9eb2ac02d4b67fc558def6727cab749a79

Observation c29c82d1-34da-4893-8c46-afb6c259177d · outbound

This paper cites SuperSim- pleNet: Unifying Unsupervised and Supervised Learning for Fast and Reliable Surface Defect Detection.

SALAD -- Semantics-Aware Logical Anomaly Detection SuperSim- pleNet: Unifying Unsupervised and Supervised Learning for Fast and Reliable Surface Defect Detection

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.875568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.443599Z digest=sha256:5dd7a767e609a862bcf4c09bfc19dc8606f8e6ddce25aa244a6f93e521677188

Observation 210d6327-9b4f-441c-a661-9fad061a16bc · outbound

This paper cites Towards To- tal Recall in Industrial Anomaly Detection.

SALAD -- Semantics-Aware Logical Anomaly Detection Towards To- tal Recall in Industrial Anomaly Detection

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.855493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.447738Z digest=sha256:3762b5ecbbc6ffac9b41407392c17b09355fa66c706138c8db2d7b8c8152714a

Observation 9beaffb6-2c5f-48f0-b8c9-4d1f06ad6241 · outbound

This paper cites Asymmetric student-teacher networks for indus- trial anomaly detection.

SALAD -- Semantics-Aware Logical Anomaly Detection Asymmetric student-teacher networks for indus- trial anomaly detection

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.840026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.452513Z digest=sha256:098a13eb3e11257f64663222d1c3ff3907dced3246827d710b728286f137de25

Observation b1479837-b3e1-43a5-a23a-ab05499f454b · outbound

This paper cites Generalised dice overlap as a deep learning loss function for highly unbalanced segmen- tations.

SALAD -- Semantics-Aware Logical Anomaly Detection Generalised dice overlap as a deep learning loss function for highly unbalanced segmen- tations

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.823657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.456856Z digest=sha256:e14f0c089c95889ab10d823ea6c6de3367d971abf7056e54327dd2e628b5a1d2

Observation cee17915-a21b-408a-a489-1a05110356c4 · outbound

This paper cites PUAD: Frustratingly simple method for robust anomaly detection.

SALAD -- Semantics-Aware Logical Anomaly Detection PUAD: Frustratingly simple method for robust anomaly detection

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.807914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.461668Z digest=sha256:964e9ac889f7b33c2429dae03baf1473354d156440446cf8a47308260c45ae14

Observation f6ffdf2d-c4ab-401d-bd0e-1a68c87b90bb · outbound

This paper cites Schmon, and Chris G.

SALAD -- Semantics-Aware Logical Anomaly Detection Schmon, and Chris G

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.791645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.467575Z digest=sha256:11ef9adc5ddb678fcdaff54209b8e7ff4702e132723b87654baa688e256ea0a8

Observation baf1ad0d-96f3-4d0d-96a2-185efd065d90 · outbound

This paper cites MemSeg: A semi- supervised method for image surface defect detection using differences and commonalities.

SALAD -- Semantics-Aware Logical Anomaly Detection MemSeg: A semi- supervised method for image surface defect detection using differences and commonalities

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.775434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.471997Z digest=sha256:faa4d43f8f13fd5ba95f46ecb0db774063f59482de6c46d26087b1e08073337a

Observation ab3478d7-6fe9-4b3d-8b60-bc6a0c36f227 · outbound

This paper cites SLSG: Industrial Image Anomaly Detection by Learning Bet- ter Feature Embeddings and One-Class Classification.Pattern Recognition, 156:110862, 2024.

SALAD -- Semantics-Aware Logical Anomaly Detection SLSG: Industrial Image Anomaly Detection by Learning Bet- ter Feature Embeddings and One-Class Classification.Pattern Recognition, 156:110862, 2024

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.760762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.476591Z digest=sha256:80888c028db4c92f3280d8aa2204321a776ed78e0cf83205c998892740828c08

Observation 97ab7533-f798-45b6-80b1-b52e107d73a6 · outbound

This paper cites Focus the discrepancy: Intra-and inter- correlation learning for image anomaly detection.

SALAD -- Semantics-Aware Logical Anomaly Detection Focus the discrepancy: Intra-and inter- correlation learning for image anomaly detection

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.745109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.483280Z digest=sha256:9845c5c27439d4c1b4a791da42c9fbfd538166bbe1699cbe94f4f9bedc3a9e8c

Observation 345a1e23-5496-44d6-8874-35c7d6a70823 · outbound

This paper cites FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows.

SALAD -- Semantics-Aware Logical Anomaly Detection FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T11:56:37.487615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:56:37.487615Z digest=sha256:e5afa50755c7276149649569450623fa2307bad89807887b260d9256d1ae128f

Observation 2c2c9701-92f3-4ff7-9a7d-9fa7b89d4ff8 · outbound

This paper cites DRAEM-A discriminatively trained reconstruction embed- ding for surface anomaly detection.

SALAD -- Semantics-Aware Logical Anomaly Detection DRAEM-A discriminatively trained reconstruction embed- ding for surface anomaly detection

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.728204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.492640Z digest=sha256:1d2935dd05058799c731b20e9917a3c61a32d3a3bc54ffc69475f00377bb23be

Observation 203def73-dc2f-48a2-8aba-b63b91e64cb4 · outbound

This paper cites Recon- struction by inpainting for visual anomaly detection.

SALAD -- Semantics-Aware Logical Anomaly Detection Recon- struction by inpainting for visual anomaly detection

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.711100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.502042Z digest=sha256:a25dbae794061ffc1941ec3a95713a533945ae0761e436be9c0d68c4f11acc91

Observation 710d1945-e563-4840-b95e-1bc778eb6ce8 · outbound

This paper cites DSR–A dual subspace re-projection network for surface anomaly de- tection.

SALAD -- Semantics-Aware Logical Anomaly Detection DSR–A dual subspace re-projection network for surface anomaly de- tection

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.691609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.507212Z digest=sha256:3e0d24c9524e7d20cd77950b287286b0aeb193d4bcf0609a60a384197c192d7d

Observation 070863c1-cdb7-48ab-bd39-6a7713c3fd67 · outbound

This paper cites Con- textual affinity distillation for image anomaly detection.

SALAD -- Semantics-Aware Logical Anomaly Detection Con- textual affinity distillation for image anomaly detection

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.674506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.511783Z digest=sha256:29b41d5d41fefd192c498a15bef7ec693452599393181c7cd620e28510fdf327

Observation ad375439-5428-47dc-b6a6-cc8ce83b4d2c · outbound

This paper cites SPot-the-Difference Self-supervised Pre- training for Anomaly Detection and Segmentation.

SALAD -- Semantics-Aware Logical Anomaly Detection SPot-the-Difference Self-supervised Pre- training for Anomaly Detection and Segmentation

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:56:37.657432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.516190Z digest=sha256:5ba550e182a39440e5f2f860da545ea231098b1f4d1f285bc782dc2e7d65487e

Observation 7e73e27f-4291-4a15-be82-642e7d7907ea · outbound

This paper cites Architectural improvements to the compositional and appearance branch might improve this.

SALAD -- Semantics-Aware Logical Anomaly Detection Architectural improvements to the compositional and appearance branch might improve this

Reference 47

Resolution
malformed identifier
raw_fallback, observed 2026-08-05T11:56:37.634687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T11:56:37.520732Z digest=sha256:4995ffb577d84c1e52f84b964d34d8bc8a5d757bdbb0483a36df05f36cf4d3d6

Pith citing papers

No inbound Pith citation observations are available.