Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Predicting Aircraft Trajectories: A Deep Generative Convolutional Recurrent Neural Networks Approach
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1812.11670.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T15:16:51.069727Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T10:32:08.363803Z
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 0e99117f-4aca-4886-b9e5-d24176d3d763 · inbound
Landing Trajectory Prediction for UAS Based on Generative Adversarial Network cites this paper.
Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Predicting Aircraft Trajectories: A Deep Generative Convolutional Recurrent Neural Networks Approach
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:16:51.069727Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7680da51-44a3-4e1e-b34f-ed8cd7b09d62 · inbound
Effective and Efficient Representation Learning for Flight Trajectories cites this paper.
Effective and Efficient Representation Learning for Flight Trajectories Predicting Aircraft Trajectories: A Deep Generative Convolutional Recurrent Neural Networks Approach
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T10:32:08.367778Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.