Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
BIGCity: A Universal Spatiotemporal Model for Unified Trajectory and Traffic State Data Analysis
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2412.00953.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T19:16:59.993154Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T11:49:52.123430Z
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 132c6fbf-4664-4e11-9bc1-fbe7f1905430 · inbound
Bridging Traffic State and Trajectory for Dynamic Road Network and Trajectory Representation Learning cites this paper.
Bridging Traffic State and Trajectory for Dynamic Road Network and Trajectory Representation Learning BIGCity: A Universal Spatiotemporal Model for Unified Trajectory and Traffic State Data Analysis
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T19:16:59.993154Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d57bcdf3-bccf-4ebb-897a-bacef79d60f9 · inbound
POI-Enhancer: An LLM-based Semantic Enhancement Framework for POI Representation Learning cites this paper.
POI-Enhancer: An LLM-based Semantic Enhancement Framework for POI Representation Learning BIGCity: A Universal Spatiotemporal Model for Unified Trajectory and Traffic State Data Analysis
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T19:42:13.865572Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ee42e290-2565-40d6-8e0f-80bb92eb91f5 · inbound
Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review cites this paper.
Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review BIGCity: A Universal Spatiotemporal Model for Unified Trajectory and Traffic State Data Analysis
Reference 235
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T11:49:52.210304Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.