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Paper Citation Record · LEDGER

Towards Robust Physical-world Backdoor Attacks on Lane Detection

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.05553.

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

pith.paper-citation-record.v1
2405.05553 v3

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 2026-08-12T06:34:41.77262+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:22:03.002617Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T00:25:48.527046Z

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 36a4f1ca-24dc-409b-8d98-8fa90def4974 · inbound

Visual Adversarial Attack on Vision-Language Models for Autonomous Driving cites this paper.

Visual Adversarial Attack on Vision-Language Models for Autonomous Driving Towards Robust Physical-world Backdoor Attacks on Lane Detection

Reference 65

Resolution
verified exact
arxiv_id, observed 2026-05-23T16:35:42.185270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-23T16:35:24.063578Z digest=sha256:cdca739ac622a85e92d16000058bdea77bd4c956340c9bf4bce6cb4528d180b2

Observation 1c66c5dc-a060-4ba5-a861-e1689c7e8b7b · inbound

CopyrightShield: Enhancing Diffusion Model Security against Copyright Infringement Attacks cites this paper.

CopyrightShield: Enhancing Diffusion Model Security against Copyright Infringement Attacks Towards Robust Physical-world Backdoor Attacks on Lane Detection

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-12T04:22:03.002617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:22:03.002617Z digest=sha256:2c1dfff10e136d1232efb721547dfdb9081c0f1b28cf1fb1593d568189d1577b

Observation 635d9011-ed56-4fa0-9c83-21513e66c517 · inbound

Robust Anti-Backdoor Instruction Tuning in LVLMs cites this paper.

Robust Anti-Backdoor Instruction Tuning in LVLMs Towards Robust Physical-world Backdoor Attacks on Lane Detection

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T11:07:37.404099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:07:37.404099Z digest=sha256:d26d5b678ca4530b8f54f4c78a243d1bbda1d93385cf648eed8d1a468e49b92e

Observation 53f68876-968c-4e4b-9105-c03019e3f982 · inbound

ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks cites this paper.

ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks Towards Robust Physical-world Backdoor Attacks on Lane Detection

Reference 2015

Resolution
unresolved
no resolver link, observed 2026-08-06T21:05:10.114257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:05:10.114257Z digest=sha256:88aff400694c6aeab859f7636170bcaeb00244aa5dc0f8f6aa646082579d1c46

Observation 17385217-f8ef-4b80-a6be-95214150c2ee · inbound

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective cites this paper.

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective Towards Robust Physical-world Backdoor Attacks on Lane Detection

Reference 76

Resolution
verified exact
local_arxiv, observed 2026-07-09T00:25:48.528297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-09T00:16:03.334057Z digest=sha256:ab413c027ba253bb5c7c4297639b3b85b6ef761ed14e39ca842152cdb3b7342f