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Paper Citation Record · LEDGER

Can We Leave Deepfake Data Behind in Training Deepfake Detector?

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.17052.

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

pith.paper-citation-record.v1
2408.17052 v1

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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:26:55.184286Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T21:35:17.850684Z

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 5769a50b-9188-4a15-8163-a547698489f2 · inbound

CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation cites this paper.

CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Can We Leave Deepfake Data Behind in Training Deepfake Detector?

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T15:26:55.184286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:26:55.184286Z digest=sha256:c4c837b4abd61d3df968f2022372816625ce627e993d44188e97a5aaa9a38d0b

Observation 3a7abbdc-409c-40fe-9358-49e634a41165 · inbound

SAGA: Source Attribution of Generative AI Videos cites this paper.

SAGA: Source Attribution of Generative AI Videos Can We Leave Deepfake Data Behind in Training Deepfake Detector?

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-17T21:35:17.853806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T21:32:27.864564Z digest=sha256:118b84185f0c4e61e33b949b0c5aaec389afc521c356b8fd8ea89034b3bf233a