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Paper Citation Record · LEDGER

Exploiting Point-Language Models with Dual-Prompts for 3D Anomaly Detection

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.11307.

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

pith.paper-citation-record.v1
2502.11307 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:22:02.427910Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T05:47:37.391352Z

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 0ff25e2b-1ea1-42a5-bf82-da1bb2205564 · 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 Exploiting Point-Language Models with Dual-Prompts for 3D Anomaly Detection

Reference 293

Resolution
unresolved
no resolver link, observed 2026-08-06T17:22:02.427910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:22:02.427910Z digest=sha256:47cec24897e853772e094c93193cd629e9b95b74ff3f4c2f4831e3f091a468c1

Observation 45839a34-f933-41cf-912a-5ab40e4df432 · inbound

C3D-AD: Toward Continual 3D Anomaly Detection via Kernel Attention with Learnable Advisor cites this paper.

C3D-AD: Toward Continual 3D Anomaly Detection via Kernel Attention with Learnable Advisor Exploiting Point-Language Models with Dual-Prompts for 3D Anomaly Detection

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-08-06T05:47:37.394945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:47:37.332942Z digest=sha256:bb0b47af1ab626b2a7a38941d094b8fe5aff2833c8de257e7e272346fb680182