Author

Miri Zilka

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#artificial intelligence Preprint Oct 2026

Evaluating Visual Realism of AI-Generated Videos with Eye Tracking

The first computational method GazeEval is proposed to predict the perceived visual realism of AI-generated videos from eye-tracking data, which achieves 71.3% accuracy in prediction, providing evidence that eye tracking data carries informative signals about how people evaluate a video.

Dan-Qing Shi, Lan Jiang, Jake Lyons et al. · 0 citations

#artificial intelligence Preprint Aug 2026

Negotiating Risk Boundaries in AI for Policing Through Mixed-Stakeholder Deliberation

Results from a mixed-stakeholder deliberation workshop bringing together 30 community representatives, police officers, and academics to assess the risks of 13 AI use cases in policing, with an explicit focus on racial bias are presented.

Mackenzie Jorgensen, Joan Reilly, A. Sutherland et al. · 0 citations