PIVOT: Physics-Grounded Verification for AI-Generated Audio-Video Detection

arXiv:2609.15562 · cs.CV, cs.AI, cs.MM · Submitted 2026-09-14 · Read on arXiv

cs.CV, cs.AI, cs.MM

Submitted: 2026-09-14

Updated: 2026-09-14

Comments: 19 pages, 4 figures, including appendix

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Verification — 57× in this paper · explained in 2 episodes
• Consistency — 37× in this paper · explained in 3 episodes
• Benchmark — 27× in this paper · explained in 2 episodes
• Accuracy — 25× in this paper · explained in 1 episode
• Verifier — 17× in this paper · explained in 2 episodes
• Calibration — 8× in this paper · explained in 7 episodes
• Physical Constraints — 7× in this paper · explained in 7 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Adaptation — 6× in this paper · explained in 1 episode
• F1 Score — 6× in this paper · explained in 3 episodes
• Alignment — 5× in this paper · explained in 1 episode
• Generative Model — 4× in this paper · explained in 2 episodes
• Generative Models — 4× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Benchmarking — 2× in this paper · explained in 3 episodes
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Ontology — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• System Identification — 1× in this paper · explained in 3 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Movie Gen: A Cast of Media Foundation Models
• Seedance 2.0: Advancing Video Generation for World Complexity
• SAVe: Self-Supervised Audio-visual Deepfake Detection Exploiting Visual Artifacts and Audio-visual Misalignment
• Generalizing Video DeepFake Detection by Self-generated Audio-Visual Pseudo-Fakes
• Do Joint Audio-Video Generation Models Understand Physics?
• PhyAVBench: A Challenging Audio Physics-Sensitivity Benchmark for Physically Grounded Text-to-Audio-Video Generation
• The DeepFake Detection Challenge (DFDC) Dataset
• So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection
• DeepfakeBench-MM: A Comprehensive Benchmark for Multimodal Deepfake Detection
• MVAD: A Benchmark Dataset for Multimodal AI-Generated Video-Audio Detection
• Track Anything: Segment Anything Meets Videos

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