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Paper Citation Record · LEDGER

AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2503.06661.

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

pith.paper-citation-record.v1
2503.06661 v1

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 2026-08-07T15:01:03.755140Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T19:16:07.323421Z

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 090d4053-1c5c-48ee-bb07-ddd1918e9096 · inbound

SD-MAD: Sign-Driven Few-shot Multi-Anomaly Detection in Medical Images cites this paper.

SD-MAD: Sign-Driven Few-shot Multi-Anomaly Detection in Medical Images AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T15:01:03.755140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:01:03.755140Z digest=sha256:e805a809001ac2059f487eb2777efe599695c415b68018a058623accf29c01ee

Observation afae3e3e-2bc1-4377-b75c-274f37e83a79 · inbound

OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning cites this paper.

OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T13:21:02.033225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:21:02.033225Z digest=sha256:546c962a72c975b5c5dc13926570ca2f284bf2b89fab081d150a927288dc6a24

Observation 3157e517-2129-469c-91db-4c64aceddda6 · 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 AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP

Reference 206

Resolution
unresolved
no resolver link, observed 2026-08-06T17:21:54.072728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:21:54.072728Z digest=sha256:5a864c3b2da8c7fa60e06ae4c5508a9aecb0fc57c39334328fc22b719a2fdf05

Observation 609b98ff-d2b8-4927-81df-0e5dd390d3c2 · inbound

Latent Anomaly Knowledge Excavation: Unveiling Sparse Sensitive Neurons in Vision-Language Models cites this paper.

Latent Anomaly Knowledge Excavation: Unveiling Sparse Sensitive Neurons in Vision-Language Models AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:51:18.544146Z

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=2026-05-10T17:25:34.942028Z digest=sha256:6455566e7d16b8aadb6bfbb6fac2cac85a1bb43db32ad2c0501d3d222e01a051

Observation 7ec6d782-4953-4e42-a47d-9f77e7b651d5 · inbound

EV-CLIP: Efficient Visual Prompt Adaptation for CLIP in Few-shot Action Recognition under Visual Challenges cites this paper.

EV-CLIP: Efficient Visual Prompt Adaptation for CLIP in Few-shot Action Recognition under Visual Challenges AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP

Reference 76

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:16:07.329098Z

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=2026-05-08T12:29:32.897198Z digest=sha256:7da281b91f600ba8904b445a3de8e78946bc4ca6ed081493497716b107d3e673