Paper Citation Record · LEDGER

Harnessing the Power of Large Vision Language Models for Synthetic Image Detection

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2404.02726.

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

pith.paper-citation-record.v1
2404.02726 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:34:11.168897Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T14:35:46.437173Z

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 cd077baf-3532-4d87-a907-e5b59cbd3914 · inbound

Unmasking Synthetic Realities in Generative AI: A Comprehensive Review of Adversarially Robust Deepfake Detection Systems cites this paper.

Unmasking Synthetic Realities in Generative AI: A Comprehensive Review of Adversarially Robust Deepfake Detection Systems Harnessing the Power of Large Vision Language Models for Synthetic Image Detection

Reference 178

Resolution: unresolved; no resolver link, observed 2026-08-06T14:34:11.168897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef2665c8-c28a-4364-8f8c-1d3eadcdfd02 · inbound

RAVID: Retrieval-Augmented Visual Detection: A Knowledge-Driven Approach for AI-Generated Image Identification cites this paper.

RAVID: Retrieval-Augmented Visual Detection: A Knowledge-Driven Approach for AI-Generated Image Identification Harnessing the Power of Large Vision Language Models for Synthetic Image Detection

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T01:04:09.636804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 769c78f1-2e6b-4323-9113-e256927168d6 · inbound

Bridging the Gap Between Ideal and Real-world Evaluation: Benchmarking AI-Generated Image Detection in Challenging Scenarios cites this paper.

Bridging the Gap Between Ideal and Real-world Evaluation: Benchmarking AI-Generated Image Detection in Challenging Scenarios Harnessing the Power of Large Vision Language Models for Synthetic Image Detection

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:02.132082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32d20571-c8ec-4e44-9394-8a71d97dc582 · inbound

Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation cites this paper.

Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation Harnessing the Power of Large Vision Language Models for Synthetic Image Detection

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:35:46.439143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.