Pith. sign in

Paper Citation Record · LEDGER

CAMOUFLAGE: Exploiting Misinformation Detection Systems Through LLM-driven Adversarial Claim Transformation

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2505.01900.

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

pith.paper-citation-record.v1
2505.01900 v1

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

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:01:04.628243Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 511dfeda-dcd8-4fa1-a7cf-9049f0455ae1 · inbound

VSF-Med:A Vulnerability Scoring Framework for Medical Vision-Language Models cites this paper.

VSF-Med:A Vulnerability Scoring Framework for Medical Vision-Language Models CAMOUFLAGE: Exploiting Misinformation Detection Systems Through LLM-driven Adversarial Claim Transformation

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T23:01:04.628243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:01:04.628243Z digest=sha256:5bc56ba63eb7b7becfa90ffece248e524e6b8284a2a134e3f93ba1a796368966

Observation 53e2952a-44d0-441c-952b-2e40ef861347 · inbound

AtomEval: Validity-Aware Atomic Evaluation of Adversarial Claim Rewriting in Fact Verification cites this paper.

AtomEval: Validity-Aware Atomic Evaluation of Adversarial Claim Rewriting in Fact Verification CAMOUFLAGE: Exploiting Misinformation Detection Systems Through LLM-driven Adversarial Claim Transformation

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-13T00:08:12.349053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T00:08:12.349053Z digest=sha256:7d900801b21176603aec77c4db51699d7c1a51ace7e9231c41348b7891e0b008

Observation b8cae10d-8d38-4150-aee7-b997d0e26e5a · inbound

Prompt Governance? On Governing Technologies Governed by Natural Language cites this paper.

Prompt Governance? On Governing Technologies Governed by Natural Language CAMOUFLAGE: Exploiting Misinformation Detection Systems Through LLM-driven Adversarial Claim Transformation

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-07-01T08:25:32.950367Z

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=2026-07-01T08:17:10.481202Z digest=sha256:d394ae1640066c9a05f427f4e028b755225aa64a7864cba8de226a867f8d784a

Observation a2a0a7cc-2a24-4476-a0f4-b1a28c7000bd · inbound

Multi-Agentic System Leveraging Open-Source LLMs to Mitigate Disinformation Threats cites this paper.

Multi-Agentic System Leveraging Open-Source LLMs to Mitigate Disinformation Threats CAMOUFLAGE: Exploiting Misinformation Detection Systems Through LLM-driven Adversarial Claim Transformation

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-06-30T06:34:19.323717Z

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=2026-06-30T06:26:50.949807Z digest=sha256:56058f73a5af9dfe6b63b21dd19008668ea59598adae785942b6ae6210c51410

Observation 594a7c10-2913-4470-9873-2067f420f504 · inbound

Large Language Models in Misinformation Ecosystems: Misuse, Defense, and Vulnerability cites this paper.

Large Language Models in Misinformation Ecosystems: Misuse, Defense, and Vulnerability CAMOUFLAGE: Exploiting Misinformation Detection Systems Through LLM-driven Adversarial Claim Transformation

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-14T12:01:22.824663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T12:01:22.824663Z digest=sha256:6c9c841afe7454c2b731cc36275e15378e87b3d622f33093b17cf178c4dbab02