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Paper Citation Record · LEDGER

Evaluating the Generalization Ability of Spatiotemporal Model in Urban Scenario

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.04740.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2410.04740 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T16:29:48.606912Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

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 003e3d6f-534a-438d-b5cb-41b869270890 · inbound

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention cites this paper.

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention Evaluating the Generalization Ability of Spatiotemporal Model in Urban Scenario

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-03T16:29:48.606912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:29:48.606912Z digest=sha256:5f48f88cc5b350bfdf0a3078b10e4635fd4010de4165753f5ebdb9b01e9fd216

Observation 150187da-d5dc-445a-bd49-b57b77a7a755 · inbound

OpFlow: Learning Opportunity-Conditioned Choice Potentials for Robust OD Flow Prediction cites this paper.

OpFlow: Learning Opportunity-Conditioned Choice Potentials for Robust OD Flow Prediction Evaluating the Generalization Ability of Spatiotemporal Model in Urban Scenario

Reference 33

Resolution
unresolved
no resolver link, observed 2026-07-12T04:11:50.269344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T04:11:50.269344Z digest=sha256:d92d7fef673393e165851609e760f36149889732de7ed56ef62c7fea90fc24c7