Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1909.10660.
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 2026-08-11T15:56:15.576861Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T21:51:31.564812Z
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 053ad437-f33b-46bd-a9bb-3ff56d48a9f8 · inbound
Higher Order Transformers: Enhancing Stock Movement Prediction On Multimodal Time-Series Data cites this paper.
Higher Order Transformers: Enhancing Stock Movement Prediction On Multimodal Time-Series Data Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T15:56:15.576861Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3e65c4a5-09b1-4484-bdef-437387b59133 · inbound
FicGCN: Unveiling the Homomorphic Encryption Efficiency from Irregular Graph Convolutional Networks cites this paper.
FicGCN: Unveiling the Homomorphic Encryption Efficiency from Irregular Graph Convolutional Networks Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:36:01.997022Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b7d64ab0-da2b-4df8-aadb-389a7d7b3cf9 · inbound
Fraud Detection in Cryptocurrency Markets with Spatio-Temporal Graph Neural Networks cites this paper.
Fraud Detection in Cryptocurrency Markets with Spatio-Temporal Graph Neural Networks Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:51:31.588348Z
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.