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Paper Citation Record · LEDGER

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment

As of 8 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2507.08367.

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

pith.paper-citation-record.v1
2507.08367 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:24:56.040704Z

measured 21 of 21 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

21 of 21 outbound references displayed

  • verified exact0
  • verified fuzzy17
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 730d52e8-3e30-44d6-9913-9b26f340f333 · outbound

This paper cites Traffic accident statistics open data,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Traffic accident statistics open data,

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 5fafe582-fb9e-4c24-8fef-54d13cfd3e91 · outbound

This paper cites The long-term effects of active training strategies on improving older drivers’ scanning in intersections: a two-year follow- up to romoser and fisher (2009),.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment The long-term effects of active training strategies on improving older drivers’ scanning in intersections: a two-year follow- up to romoser and fisher (2009),

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:25:19.387126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 8de85bb4-60de-4ad4-b8e8-02400602e2ff · outbound

This paper cites an unresolved cited work.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:25:19.356549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 0ef5bd47-b03b-4a26-ac31-30db872c91f2 · outbound

This paper cites Are inter- ventions effective at improving driving in older drivers?: A systematic review,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Are inter- ventions effective at improving driving in older drivers?: A systematic review,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:57.602044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 478832af-9266-4a81-b0d0-58eed7ac2bd4 · outbound

This paper cites The use of monitor- ing and feedback devices in driving: An assessment of acceptability and its key determinants,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment The use of monitor- ing and feedback devices in driving: An assessment of acceptability and its key determinants,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:57.314328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 56cfb709-8226-4653-b591-36d039798285 · outbound

This paper cites Study on driver agent based on analysis of driving instruction data—driver agent for encouraging safe driving behavior (1)—,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Study on driver agent based on analysis of driving instruction data—driver agent for encouraging safe driving behavior (1)—,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:57.193048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c2712c5a-680d-4e59-8b04-27c294acf73e · outbound

This paper cites How ai from automated driving systems can contribute to the assessment of human driving behavior,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment How ai from automated driving systems can contribute to the assessment of human driving behavior,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:57.067897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f2577956-5a2b-4dec-b939-e0c965af8010 · outbound

This paper cites Integrating visual large language model and reasoning chain for driver behavior analysis and risk assessment,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Integrating visual large language model and reasoning chain for driver behavior analysis and risk assessment,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:56.931088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 3586df93-3879-4c8e-9229-ddf6da30904e · outbound

This paper cites Exploring the potential of multi-modal ai for driving hazard prediction,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Exploring the potential of multi-modal ai for driving hazard prediction,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:56.830016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 605dfac7-b8fd-4eac-8698-a8287116497d · outbound

This paper cites Surrealdriver: Designing llm-powered generative driver agent framework based on human drivers’ driving-thinking data,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Surrealdriver: Designing llm-powered generative driver agent framework based on human drivers’ driving-thinking data,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:56.760997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 935b40bf-3880-4422-8d1e-09dda03fc379 · outbound

This paper cites Drivegpt4: Interpretable end-to-end autonomous driving via large language model,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Drivegpt4: Interpretable end-to-end autonomous driving via large language model,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:56.695467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation cf7d8e0e-8538-41ff-a8be-8861e98c2631 · outbound

This paper cites Chatbot and fatigued driver: Exploring the use of llm-based voice assistants for driving fatigue,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Chatbot and fatigued driver: Exploring the use of llm-based voice assistants for driving fatigue,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:56.599215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 52fa2c84-060a-4339-a564-bc74e6acac1f · outbound

This paper cites Older driver perception-reaction time for intersection sight distance and object detection, volume i,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Older driver perception-reaction time for intersection sight distance and object detection, volume i,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:56.513177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 322f1ce8-98ae-4432-831d-4fa3eab4a2cf · outbound

This paper cites Urban and rural differences in older drivers’ failure to stop at stop signs,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Urban and rural differences in older drivers’ failure to stop at stop signs,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:56.449192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a0be0d70-ce4d-4d72-a019-a278068b27d6 · outbound

This paper cites Left turns by older drivers with vision impairment: A naturalistic driving study,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Left turns by older drivers with vision impairment: A naturalistic driving study,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:56.375692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation ede48376-8ba2-4ffe-acf2-27f9cfee1a87 · outbound

This paper cites Large lan- guage models are zero-shot reasoners,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Large lan- guage models are zero-shot reasoners,

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T18:24:55.705840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a6bd2c5f-bb17-471e-821b-92698d038729 · outbound

This paper cites Language mod- els are few-shot learners,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Language mod- els are few-shot learners,

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T18:24:55.777890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8da40cf6-3837-4f95-af12-b276475c9050 · outbound

This paper cites NuPlanQA: A Large-Scale Dataset and Benchmark for Multi-View Driving Scene Understanding in Multi-Modal Large Language Models.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment NuPlanQA: A Large-Scale Dataset and Benchmark for Multi-View Driving Scene Understanding in Multi-Modal Large Language Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T18:24:55.861011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e3a7fa0f-3434-448b-9b38-36fe97a46782 · outbound

This paper cites When technology tells you how you drive—-truck drivers’ attitudes towards feedback by technology,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment When technology tells you how you drive—-truck drivers’ attitudes towards feedback by technology,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:56.308131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation e4994e3f-bc98-428d-9dcc-854f0a78ff09 · outbound

This paper cites Exploring whether chatgpt-4 with image analysis capabilities can diagnose os- teosarcoma from x-ray images,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Exploring whether chatgpt-4 with image analysis capabilities can diagnose os- teosarcoma from x-ray images,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:56.243635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation ccf85c7a-d310-417f-98ad-a0de803d9d21 · outbound

This paper cites Unlocking the potential of medical imaging with chatgpt’s intelligent diagnostics,.

Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment Unlocking the potential of medical imaging with chatgpt’s intelligent diagnostics,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:24:56.149541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Pith citing papers

No inbound Pith citation observations are available.