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Paper Citation Record · LEDGER

UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.06370.

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

pith.paper-citation-record.v1
2406.06370 v2

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:43:53.034369Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:00:16.653678Z

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 80a78b90-59ec-43a0-9dad-eb2e8c3343ca · inbound

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models cites this paper.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T12:43:53.034369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:43:53.034369Z digest=sha256:2915af2f25f26551e1c92872136ad7d7d881d50a39aa98eb06f8662f22e67f68

Observation 0e5ba2e6-e5fb-4eb8-ab8e-195b96f2f01f · inbound

NSF-HRPT: Neural Semantic Field meets Hierarchical Risk Perception Tree for Safety-Critical Scenario Assessment cites this paper.

NSF-HRPT: Neural Semantic Field meets Hierarchical Risk Perception Tree for Safety-Critical Scenario Assessment UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:00:16.761916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:00:14.477494Z digest=sha256:cc4ce41b853ab433e56a63887d6f899b0f97310d10c39db0b38964964156ff5b