Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Distinguish Any Fake Videos: Unleashing the Power of Large-scale Data and Motion Features
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2405.15343.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T21:12:23.041980Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T10:01:13.543622Z
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 c319a059-66e1-4731-a2a8-899938edc137 · inbound
Survey on AI-Generated Media Detection: From Non-MLLM to MLLM cites this paper.
Survey on AI-Generated Media Detection: From Non-MLLM to MLLM Distinguish Any Fake Videos: Unleashing the Power of Large-scale Data and Motion Features
Reference 146
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T21:12:23.041980Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b0eb5f8-0040-4761-aafd-288c4e552ac2 · inbound
Unmasking Puppeteers: Leveraging Biometric Leakage to Expose Impersonation in AI-Based Videoconferencing cites this paper.
Unmasking Puppeteers: Leveraging Biometric Leakage to Expose Impersonation in AI-Based Videoconferencing Distinguish Any Fake Videos: Unleashing the Power of Large-scale Data and Motion Features
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T10:01:13.548884Z
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.
Observation 177902d4-66e0-4d76-959d-212ad2061867 · inbound
RobustSora: De-Watermarked Benchmark for Robust AI-Generated Video Detection cites this paper.
RobustSora: De-Watermarked Benchmark for Robust AI-Generated Video Detection Distinguish Any Fake Videos: Unleashing the Power of Large-scale Data and Motion Features
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-16T23:13:39.320254Z
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.
Observation d02b7435-0fd8-4ade-8efd-c3f841cfd0e3 · inbound
ATSS: Detecting AI-Generated Videos via Anomalous Temporal Self-Similarity cites this paper.
ATSS: Detecting AI-Generated Videos via Anomalous Temporal Self-Similarity Distinguish Any Fake Videos: Unleashing the Power of Large-scale Data and Motion Features
Reference 44
- Resolution
- verified exact
- orphan_title_repair, observed 2026-05-13T17:18:34.638529Z
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.
Observation 1deeacae-a37e-4d0b-8da2-d85c6d3337e3 · inbound
All in One: A Unified Synthetic Data Pipeline for Multimodal Video Understanding cites this paper.
All in One: A Unified Synthetic Data Pipeline for Multimodal Video Understanding Distinguish Any Fake Videos: Unleashing the Power of Large-scale Data and Motion Features
Reference 48
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T10:31:03.972270Z
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.
Observation 30e330d7-67ea-4cc7-9d45-ffd251f0eca8 · inbound
CMTA: Leveraging Cross-Modal Temporal Artifacts for Generalizable AI-Generated Video Detection cites this paper.
CMTA: Leveraging Cross-Modal Temporal Artifacts for Generalizable AI-Generated Video Detection Distinguish Any Fake Videos: Unleashing the Power of Large-scale Data and Motion Features
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T15:16:09.989151Z
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.
Observation 62b601bc-ef4b-4ec3-83e8-c3e75d85e45f · inbound
SafeGuard: A Multi-Agent Perception-Reasoning Framework for Social-Risk AI-Generated Video Detection cites this paper.
SafeGuard: A Multi-Agent Perception-Reasoning Framework for Social-Risk AI-Generated Video Detection Distinguish Any Fake Videos: Unleashing the Power of Large-scale Data and Motion Features
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T05:07:18.364787Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 92528d57-c883-4ade-bc80-5ba78e56beea · inbound
Detecting AI-Generated Video: A Vision-Language Dual-View Survey cites this paper.
Detecting AI-Generated Video: A Vision-Language Dual-View Survey Distinguish Any Fake Videos: Unleashing the Power of Large-scale Data and Motion Features
Reference 198
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T09:16:37.881212Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2f8d39e8-276d-49a2-8636-fb6762e0d77d · inbound
V-FIND: Revealing the Intrinsic Forgery Knowledge Encoded in Video Forgery Detectors cites this paper.
V-FIND: Revealing the Intrinsic Forgery Knowledge Encoded in Video Forgery Detectors Distinguish Any Fake Videos: Unleashing the Power of Large-scale Data and Motion Features
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T04:21:37.872486Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.