Paper Citation Record · LEDGER

Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.07320.

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

pith.paper-citation-record.v1
2402.07320 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 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:11:03.512976Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T23:07:27.076849Z

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 d721257e-80b0-41a7-8c6c-778e71faacee · inbound

Technical Report for Argoverse2 Scenario Mining Challenges on Iterative Error Correction and Spatially-Aware Prompting cites this paper.

Technical Report for Argoverse2 Scenario Mining Challenges on Iterative Error Correction and Spatially-Aware Prompting Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T05:11:03.512976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32284977-fabe-48c3-a514-49f581538853 · inbound

A New Perspective On AI Safety Through Control Theory Methodologies cites this paper.

A New Perspective On AI Safety Through Control Theory Methodologies Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-06T21:38:25.627111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb49cc5e-3b68-4d8e-966e-a8a43cde0cff · inbound

Safety-Critical Learning for Long-Tail Events: The TUM Traffic Accident Dataset cites this paper.

Safety-Critical Learning for Long-Tail Events: The TUM Traffic Accident Dataset Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-05T18:27:31.854242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8489d224-2f08-4f83-87a8-eff49a1422c6 · inbound

Looking and Listening Inside and Outside: Multimodal Artificial Intelligence Systems for Driver Safety Assessment and Intelligent Vehicle Decision-Making cites this paper.

Looking and Listening Inside and Outside: Multimodal Artificial Intelligence Systems for Driver Safety Assessment and Intelligent Vehicle Decision-Making Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-16T05:57:24.395490Z

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 b7ff97df-4ca9-4b1c-9f66-411ce3fcb10f · inbound

Vision-Language Work Zone Intelligence for Safety-Critical Speed Regulation of Mixed-Autonomy Vehicles in Dynamic Environments cites this paper.

Vision-Language Work Zone Intelligence for Safety-Critical Speed Regulation of Mixed-Autonomy Vehicles in Dynamic Environments Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-02T23:07:27.078707Z

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.