Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2307.00495.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T18:37:07.063869Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T01:17:30.943406Z
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 fb7af375-7694-4880-84c8-c005ac35f965 · inbound
Unveiling the Inflexibility of Adaptive Embedding in Traffic Forecasting cites this paper.
Unveiling the Inflexibility of Adaptive Embedding in Traffic Forecasting STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T18:37:07.063869Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9523d93f-cf9e-4f08-b6d6-69b016243048 · inbound
STDCformer: A Transformer-Based Model with a Spatial-Temporal Causal De-Confounding Strategy for Crowd Flow Prediction cites this paper.
STDCformer: A Transformer-Based Model with a Spatial-Temporal Causal De-Confounding Strategy for Crowd Flow Prediction STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T22:59:58.725153Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d31d25ec-6639-4ad5-becb-9a1b5cc76ff0 · inbound
ADFormer: Aggregation Differential Transformer for Passenger Demand Forecasting cites this paper.
ADFormer: Aggregation Differential Transformer for Passenger Demand Forecasting STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:24:38.110006Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 819120ae-877b-472a-88ee-eceedf331866 · inbound
From Coarse to Fine: Managing Temporal Granularity in Spatio-Temporal Data for Fine-Grained Traffic Prediction cites this paper.
From Coarse to Fine: Managing Temporal Granularity in Spatio-Temporal Data for Fine-Grained Traffic Prediction STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T01:17:30.944979Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b771021b-4af3-4b62-a5ea-7dff5c498a66 · inbound
Efficient Traffic Prediction at Scale: A Systematic Study of STGCN Architectural Depth cites this paper.
Efficient Traffic Prediction at Scale: A Systematic Study of STGCN Architectural Depth STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T00:07:27.722776Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.