Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2403.02600.
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 2026-08-11T20:43:51.890716Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T08:33:15.691120Z
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 22a31b17-17bc-4f55-a0a0-1fe9efd60e5a · inbound
Memory-enhanced Invariant Prompt Learning for Urban Flow Prediction under Distribution Shifts cites this paper.
Memory-enhanced Invariant Prompt Learning for Urban Flow Prediction under Distribution Shifts TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T20:43:51.890716Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ed07970-4ae4-4fdd-a0fd-1c8d9bd560e5 · inbound
TSNN: A Non-parametric and Interpretable Framework for Traffic Time Series Forecasting cites this paper.
TSNN: A Non-parametric and Interpretable Framework for Traffic Time Series Forecasting TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts
Reference 45
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T02:06:15.264776Z
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.
Observation ea460a36-e9cc-4b9b-a4c8-0cf57affccdc · inbound
Graph-Conditioned Mixture of Graph Neural Network Experts for Traffic Forecasting cites this paper.
Graph-Conditioned Mixture of Graph Neural Network Experts for Traffic Forecasting TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T08:33:15.692652Z
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.