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Paper Citation Record · LEDGER

Learning Traffic Crashes as Language: Datasets, Benchmarks, and What-if Causal Analyses

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.10789.

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

pith.paper-citation-record.v1
2406.10789 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:22:46.458202Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T23:06:20.643231Z

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 e747f55a-3174-4d8c-8590-34e76b368e5a · inbound

CrashSage: A Large Language Model-Centered Framework for Contextual and Interpretable Traffic Crash Analysis cites this paper.

CrashSage: A Large Language Model-Centered Framework for Contextual and Interpretable Traffic Crash Analysis Learning Traffic Crashes as Language: Datasets, Benchmarks, and What-if Causal Analyses

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-15T23:22:46.458202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:22:46.458202Z digest=sha256:10aa2b12440ff7dcd4a93d851c5439dce39f03a9be92ca10cbec398dc22ffed7

Observation 7b6c24ea-bf77-406f-a2c6-af9bcc316956 · inbound

Advanced Crash Causation Analysis for Freeway Safety: A Large Language Model Approach to Identifying Key Contributing Factors cites this paper.

Advanced Crash Causation Analysis for Freeway Safety: A Large Language Model Approach to Identifying Key Contributing Factors Learning Traffic Crashes as Language: Datasets, Benchmarks, and What-if Causal Analyses

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T21:24:04.272455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:24:04.272455Z digest=sha256:ad7eb58591e019b62b08c50390deb244bf937859abd55da05307c7ca76c177e7

Observation 70f96399-eacc-4013-b114-062c9d1c8db0 · inbound

Predicting person-level injury severity using crash narratives: A balanced approach with roadway classification and natural language process techniques cites this paper.

Predicting person-level injury severity using crash narratives: A balanced approach with roadway classification and natural language process techniques Learning Traffic Crashes as Language: Datasets, Benchmarks, and What-if Causal Analyses

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-15T16:12:54.074249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:12:54.074249Z digest=sha256:8e3d0cc1804c0e763a59fb7c7dbf44790feec9f29bc49a7bb02075c2e4cec540

Observation beccc242-6eb2-4b94-98ea-a94d1614a42c · inbound

An Agentic Workflow for Detecting Personally Identifiable Information in Crash Narratives cites this paper.

An Agentic Workflow for Detecting Personally Identifiable Information in Crash Narratives Learning Traffic Crashes as Language: Datasets, Benchmarks, and What-if Causal Analyses

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-10T13:45:28.677775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T13:40:33.026198Z digest=sha256:6a49a811b98b73bd448ae21b6c047ae5e44fe40b66bef64ce22b306a1d4f0ce2

Observation 6bcae783-0d68-4367-9181-2b28c306a822 · inbound

TrafficRAG: A Multimodal RAG Framework for Traffic Accident Liability Determination cites this paper.

TrafficRAG: A Multimodal RAG Framework for Traffic Accident Liability Determination Learning Traffic Crashes as Language: Datasets, Benchmarks, and What-if Causal Analyses

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-01T23:06:20.647186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-28T14:39:27.242094Z digest=sha256:2c99931b8c9a4c3f95c0be3a7c133c98438fed46965458574e9ef340e60fb2cc