Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1808.03314.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:40:26.633982Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T22:32:12.603941Z
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 8cad9e5a-b740-4c71-a0e2-f2da11a762db · inbound
Electroweak diboson production in association with a high-mass dijet system in semileptonic final states from $pp$ collisions at $\sqrt{s} = 13$ TeV with the ATLAS detector cites this paper.
Electroweak diboson production in association with a high-mass dijet system in semileptonic final states from $pp$ collisions at $\sqrt{s} = 13$ TeV with the ATLAS detector Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network
Reference 98
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T22:32:12.606771Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f8616564-0c99-4489-a1ef-8003eed24490 · inbound
Machine Learning-Based Anomaly Detection of Correlated Sensor Data: An Integrated Principal Component Analysis-Autoencoder Approach cites this paper.
Machine Learning-Based Anomaly Detection of Correlated Sensor Data: An Integrated Principal Component Analysis-Autoencoder Approach Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:40:26.633982Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 816e96fb-b717-4815-a7df-e13631663ad9 · inbound
Model-Agnostic FDR Control via Group Gaussian Mirror and Permutation SHAP cites this paper.
Model-Agnostic FDR Control via Group Gaussian Mirror and Permutation SHAP Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T00:41:05.407198Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.