Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Fighting Fire with Fire: Adversarial Prompting to Generate a Misinformation Detection Dataset
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2401.04481.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:01:04.668572Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T20:03:54.756262Z
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 b76f13a8-04f9-4610-8be0-0da2f9c9cc80 · 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 Fighting Fire with Fire: Adversarial Prompting to Generate a Misinformation Detection Dataset
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:01:04.668572Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dfa5b69c-f66a-4c87-8026-0a66dd894014 · inbound
A Survey on Proactive Defense Strategies Against Misinformation in Large Language Models cites this paper.
A Survey on Proactive Defense Strategies Against Misinformation in Large Language Models Fighting Fire with Fire: Adversarial Prompting to Generate a Misinformation Detection Dataset
Reference 55
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T20:03:54.801797Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation c4f58dd4-db12-4afa-8c07-9cec462a80e3 · inbound
Angry but Accurate: Detecting and Profiling the Counter-Misinformation Ecosystem on Twitter cites this paper.
Angry but Accurate: Detecting and Profiling the Counter-Misinformation Ecosystem on Twitter Fighting Fire with Fire: Adversarial Prompting to Generate a Misinformation Detection Dataset
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T06:16:59.229087Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.