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Paper Citation Record · LEDGER

Pushing the Limits of Fewshot Anomaly Detection in Industry Vision: Graphcore

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2301.12082.

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

pith.paper-citation-record.v1
2301.12082 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T16:32:10.021545Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:17:28.735497Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 036edc68-14ad-412b-a81f-448749dc1dc4 · inbound

Multimodal Task Representation Memory Bank vs. Catastrophic Forgetting in Anomaly Detection cites this paper.

Multimodal Task Representation Memory Bank vs. Catastrophic Forgetting in Anomaly Detection Pushing the Limits of Fewshot Anomaly Detection in Industry Vision: Graphcore

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-08T16:32:10.021545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T16:32:10.021545Z digest=sha256:f421472dee69e7bc2608c7f9414652d5257c0857b52074bde37c2cd92e0968f6

Observation 07083c70-f381-433a-9e41-75e0eb3855a7 · inbound

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

DictAS: A Framework for Class-Generalizable Few-Shot Anomaly Segmentation via Dictionary Lookup Pushing the Limits of Fewshot Anomaly Detection in Industry Vision: Graphcore

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-05T18:59:09.587820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T18:59:09.587820Z digest=sha256:2eb5d029a3ed699e2784320671a86966e6d97635529de5b4b78151a732cb1ef4

Observation 81010138-53d2-4c2c-85f3-65005d3c6847 · inbound

Generative Model-Based Feature Attention Module for Video Action Analysis cites this paper.

Generative Model-Based Feature Attention Module for Video Action Analysis Pushing the Limits of Fewshot Anomaly Detection in Industry Vision: Graphcore

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-05T19:03:31.756784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:03:31.756784Z digest=sha256:333b6cb1dacc7df5ff60152cedc37f560a4e77c483e8c961525d49ed35f5f3b8

Observation c3a60db1-d478-4494-9f26-72276cbc68f0 · inbound

SubspaceAD: Training-Free Few-Shot Anomaly Detection via Subspace Modeling cites this paper.

SubspaceAD: Training-Free Few-Shot Anomaly Detection via Subspace Modeling Pushing the Limits of Fewshot Anomaly Detection in Industry Vision: Graphcore

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-15T18:50:16.731370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T18:48:08.212050Z digest=sha256:85e7ff5c39f8735c5b3d25aa2e714ff3f75f8e30df7faca239c07d304748372c

Observation b3e41ad7-0d8d-4b67-a87c-d464ed8a2629 · inbound

Visual Prompting Meets Feature Reconstruction-Based Anomaly Detection with Dual-Teacher Supervision cites this paper.

Visual Prompting Meets Feature Reconstruction-Based Anomaly Detection with Dual-Teacher Supervision Pushing the Limits of Fewshot Anomaly Detection in Industry Vision: Graphcore

Reference 4

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T00:17:28.737006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T17:23:13.494169Z digest=sha256:7011ba18f60902fc0f6921a3a4e5ff66a57221fb454ddd75fdad5c962f5e9edd