Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
GCNNMatch: Graph Convolutional Neural Networks for Multi-Object Tracking via Sinkhorn Normalization
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2010.00067.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T15:35:59.466394Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T11:56:55.178140Z
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 b51e984c-90ba-4039-8143-53d2c28ae76a · inbound
Heterogeneous Graph Transformer for Multiple Tiny Object Tracking in RGB-T Videos cites this paper.
Heterogeneous Graph Transformer for Multiple Tiny Object Tracking in RGB-T Videos GCNNMatch: Graph Convolutional Neural Networks for Multi-Object Tracking via Sinkhorn Normalization
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T15:35:59.466394Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d98f767b-7c7b-4885-8b18-3160387f4533 · inbound
HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery cites this paper.
HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery GCNNMatch: Graph Convolutional Neural Networks for Multi-Object Tracking via Sinkhorn Normalization
Reference 9
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T11:56:55.179964Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.