Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Enhancing Traffic Prediction with Textual Data Using Large Language Models
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2405.06719.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:07:09.604151Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T13:35:46.224334Z
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 5beace35-9b7e-4382-85ba-6a2be46151f6 · 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 Enhancing Traffic Prediction with Textual Data Using Large Language Models
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:07:09.604151Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e9547eb5-d812-4d8c-a177-8ed0c1bf1610 · inbound
Earth Science Foundation Models: From Perception to Reasoning and Discovery cites this paper.
Earth Science Foundation Models: From Perception to Reasoning and Discovery Enhancing Traffic Prediction with Textual Data Using Large Language Models
Reference 271
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T22:08:03.254962Z
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 09dde805-d323-4f6b-acd2-585bd313c077 · inbound
Earth Science Foundation Models: From Perception to Reasoning and Discovery cites this paper.
Earth Science Foundation Models: From Perception to Reasoning and Discovery Enhancing Traffic Prediction with Textual Data Using Large Language Models
Reference 271
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T13:35:46.225853Z
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.