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Paper Citation Record · LEDGER

Generative AI Security: Challenges and Countermeasures

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.12617.

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

pith.paper-citation-record.v1
2402.12617 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:32:12.052212Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T22:24:24.078464Z

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 6c1da230-3aea-4950-b478-aa8847102d52 · inbound

Practical, Generalizable and Robust Backdoor Attacks on Text-to-Image Diffusion Models cites this paper.

Practical, Generalizable and Robust Backdoor Attacks on Text-to-Image Diffusion Models Generative AI Security: Challenges and Countermeasures

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T05:32:12.052212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:32:12.052212Z digest=sha256:b570f77ff48891008f5353204e23f9a35701a6a8867ad0ab0447d5be82f602ef

Observation d9ced9b5-dfba-486c-9578-eca36764c4f8 · inbound

A Real-Time, Self-Tuning Moderator Framework for Adversarial Prompt Detection cites this paper.

A Real-Time, Self-Tuning Moderator Framework for Adversarial Prompt Detection Generative AI Security: Challenges and Countermeasures

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-05T22:24:24.081871Z

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.

source=pdf_text observed=2026-08-05T22:24:23.354632Z digest=sha256:ca8f2798d08d6c6e1d9b54101d52680b7d32ea90982e14baad523c55c8b2c8ea