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Paper Citation Record · LEDGER

What Would Trojans Do? Exploiting Partial-Information Vulnerabilities in Autonomous Vehicle Sensing

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2303.03470.

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

pith.paper-citation-record.v1
2303.03470 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:57:16.069474Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T21:28:58.794805Z

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 6d73d100-67f5-44bb-af6a-cb437168f615 · inbound

A Survey on Adversarial Robustness of LiDAR-based Machine Learning Perception in Autonomous Vehicles cites this paper.

A Survey on Adversarial Robustness of LiDAR-based Machine Learning Perception in Autonomous Vehicles What Would Trojans Do? Exploiting Partial-Information Vulnerabilities in Autonomous Vehicle Sensing

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-12T15:57:16.069474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:57:16.069474Z digest=sha256:86adffc923bb2d5ed05564101764562e0e22f8ebb4022a126ce663a94b3141a5

Observation 509ecec7-a52c-4220-ab9d-5948afa4d115 · inbound

Assured Autonomy with Neuro-Symbolic Perception cites this paper.

Assured Autonomy with Neuro-Symbolic Perception What Would Trojans Do? Exploiting Partial-Information Vulnerabilities in Autonomous Vehicle Sensing

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T13:40:20.183488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:40:20.183488Z digest=sha256:3c83b062ac075be9adbb9e568467dd4a64bcf17ed7abb8c552560bb451e77e4a

Observation 6c7e7beb-ba9f-477b-af76-3279ec8a716c · inbound

Trusted Data Fusion, Multi-Agent Autonomy, Autonomous Vehicles cites this paper.

Trusted Data Fusion, Multi-Agent Autonomy, Autonomous Vehicles What Would Trojans Do? Exploiting Partial-Information Vulnerabilities in Autonomous Vehicle Sensing

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T14:46:10.816888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:46:10.816888Z digest=sha256:46adfd2369707403ea44d02062b3965889a6025e520129e61d9560406e31a846

Observation 2b54259c-8351-48b8-be66-7b4fd6286137 · inbound

Anywhere, Any-Stymie: Remote Activation of Trojan Malware on LiDAR with Modulated Signals cites this paper.

Anywhere, Any-Stymie: Remote Activation of Trojan Malware on LiDAR with Modulated Signals What Would Trojans Do? Exploiting Partial-Information Vulnerabilities in Autonomous Vehicle Sensing

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-07-03T21:28:58.796209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-27T00:33:03.730462Z digest=sha256:af7bd485158371db8cfcb2398b4cd36ed1bc34c02bc3f7a04def54dece7ea6d6