Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Comprehensive Survey on Deep-Learning-based Vehicle Re-Identification: Models, Data Sets and Challenges
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.10643.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T00:57:11.271161Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T00:57:13.487930Z
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 e54d93aa-003e-43c0-8d9b-5175f3a372ca · inbound
CLIPVehicle: A Unified Framework for Vision-based Vehicle Search cites this paper.
CLIPVehicle: A Unified Framework for Vision-based Vehicle Search A Comprehensive Survey on Deep-Learning-based Vehicle Re-Identification: Models, Data Sets and Challenges
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T00:57:13.538232Z
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.
Observation bc5b2566-4b29-417d-88ad-59c87a3c3423 · inbound
Rethinking Multi-Branch and Cross-Backbone Fusion for Vehicle Re-Identification in the Foundation-Model Era cites this paper.
Rethinking Multi-Branch and Cross-Backbone Fusion for Vehicle Re-Identification in the Foundation-Model Era A Comprehensive Survey on Deep-Learning-based Vehicle Re-Identification: Models, Data Sets and Challenges
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T05:59:03.515543Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.