Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Fairness in Autonomous Driving: Towards Understanding Confounding Factors in Object Detection under Challenging Weather
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.00219.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-22T23:06:39.764310Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T23:07:14.197009Z
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 5ba56216-dc45-4b4f-ac13-7cc04eb21aa9 · inbound
RESFL: An Uncertainty-Aware Framework for Responsible Federated Learning by Balancing Privacy, Fairness and Utility cites this paper.
RESFL: An Uncertainty-Aware Framework for Responsible Federated Learning by Balancing Privacy, Fairness and Utility Fairness in Autonomous Driving: Towards Understanding Confounding Factors in Object Detection under Challenging Weather
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T23:07:14.199572Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 0bc22a07-9592-4437-bc7d-50620d028e83 · inbound
VLM-VPI: A Vision-Language Reasoning Framework for Improving Automated Vehicle-Pedestrian Interactions cites this paper.
VLM-VPI: A Vision-Language Reasoning Framework for Improving Automated Vehicle-Pedestrian Interactions Fairness in Autonomous Driving: Towards Understanding Confounding Factors in Object Detection under Challenging Weather
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T22:51:23.219435Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.