Paper Citation Record · LEDGER

Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2503.13502.

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

pith.paper-citation-record.v1
2503.13502 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:36:48.555055Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T21:22:59.053639Z

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 310ef7c7-f971-4d69-9794-0d285f051129 · inbound

Physics-Guided Learning of Meteorological Dynamics for Weather Downscaling and Forecasting cites this paper.

Physics-Guided Learning of Meteorological Dynamics for Weather Downscaling and Forecasting Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T15:36:48.555055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6be8a144-ebf7-424b-bab4-a262aef07469 · inbound

A Modular Multitask Reasoning Framework Integrating Spatio-temporal Models and LLMs cites this paper.

A Modular Multitask Reasoning Framework Integrating Spatio-temporal Models and LLMs Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T23:01:34.577356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 199b33ba-b874-464b-832e-45d0ce9e69ce · inbound

Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applications cites this paper.

Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applications Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-06T21:07:10.915325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84d3a2ec-cb5c-4134-82ef-843a2f4b39b8 · inbound

PlaceRep: Geospatial Place Representation Learning from Large-Scale Point-of-Interest Data cites this paper.

PlaceRep: Geospatial Place Representation Learning from Large-Scale Point-of-Interest Data Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T22:53:14.812865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9af14fc2-0088-41df-89fe-c5feae07aee2 · inbound

PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting cites this paper.

PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:21:25.976357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e89438a8-2cc6-4f11-8f74-0380ac6d23a8 · inbound

PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting cites this paper.

PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:22:59.055621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.