Scaling Synthetic Veo Data for Zero-Shot Video Model Transfer on Kinetics-700

Abstract

Abstract: This report synthesises findings from 13 peer-reviewed papers addressing the following research question: What is the impact of scaling the size of synthetic Veo-generated training data on the zero-shot transfer accuracy of foundation video models, as evaluated by success rates on the Kinetics-700. 6 claims were extracted from source literature; 4 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 7.2/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research Question

What is the impact of scaling the size of synthetic Veo-generated training data on the zero-shot transfer accuracy of foundation video models, as evaluated by success rates on the Kinetics-700 benchmark?

Verification Level

Descriptive public verification status only; aggregate claim counts are public, but individual claim records are not exposed here.

Quality Tier

Descriptive public triage only; this tier does not alter current publication or DOI behavior.

Quality Dimensions

Automated triage signals derived from public fields; not human peer review or independent validation.

Correction Record

Public corrections are additive records. Current status does not claim the synthesis is error-free.

Provenance