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Paper Citation Record · LEDGER

The 9th AI City Challenge

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2508.13564.

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

pith.paper-citation-record.v1
2508.13564 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:15:47.227259Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T13:58:21.634120Z

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 0852522f-220d-4bd5-9a08-4c80ae01eeb2 · inbound

Fully Distributed Multi-View 3D Tracking in Real-Time cites this paper.

Fully Distributed Multi-View 3D Tracking in Real-Time The 9th AI City Challenge

Reference 41

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T13:58:21.635548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-27T07:24:34.671175Z digest=sha256:c439994115a2466eb9ee179ea092edf7cfb0006ebe67fdaa30b05db43e497c15

Observation 29d4a380-1a16-4a98-8429-5a086a1e3ddd · inbound

From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning cites this paper.

From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning The 9th AI City Challenge

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-14T04:15:47.227259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:15:47.227259Z digest=sha256:e578d0b15be91de978ec88bed9b876f0b24fbdd94c44526e92d20c51889d5a0d