Pith. sign in

Paper Citation Record · LEDGER

Vision-based autonomous structural damage detection using data-driven methods

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2501.16662.

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

pith.paper-citation-record.v1
2501.16662 v2

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 2026-08-04T08:22:55.076118Z

measured 0 of 1 external citation measurements

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

Source: cited_works

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 8d69186f-e06a-412f-a956-a6fd2a32cb4d · inbound

An Experimental Study of Trojan Vulnerabilities in UAV Autonomous Landing cites this paper.

An Experimental Study of Trojan Vulnerabilities in UAV Autonomous Landing Vision-based autonomous structural damage detection using data-driven methods

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-04T08:22:55.076118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:22:55.076118Z digest=sha256:9f8fbc85b14cb33c4f88761296d24c2cec6fa5e8ead7c5886685f44c1ac2f715

Observation 830cb3ae-2d28-444e-8d7a-9ab70d9800ed · inbound

Seeing the Unseen: Towards Training-Free Inspection for Wind Turbine Blades Using Knowledge-Augmented Vision Language Models cites this paper.

Seeing the Unseen: Towards Training-Free Inspection for Wind Turbine Blades Using Knowledge-Augmented Vision Language Models Vision-based autonomous structural damage detection using data-driven methods

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-04T08:07:26.798836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:07:26.798836Z digest=sha256:2ff0774f882a7eceb0b76efc614c26befdd7046002084773894271bff908a246