TRACE achieves 97% macro F1 on temporal out-of-distribution prediction of organizational exploit targets using contrastive learning on a 129k-sample multi-source dataset, outperforming 17 baselines.
Exploring Emerging Hacker Assets and Key Hackers for Proactive Cyber Threat Intelligence,
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Deep learning models analyzing temporal facial expressions and head movements in interview videos explained 91% and 84% of variance in self-reported honest and deceptive impression management, outperforming human interviewers' correlations with the same self-reports.
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Vendor-Conditioned Contrastive Learning for Predicting Organizational Cyber Threat Targets
TRACE achieves 97% macro F1 on temporal out-of-distribution prediction of organizational exploit targets using contrastive learning on a 129k-sample multi-source dataset, outperforming 17 baselines.
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Artificial Intelligence can Recognize Whether a Job Applicant is Selling and/or Lying According to Facial Expressions and Head Movements Much More Correctly Than Human Interviewers
Deep learning models analyzing temporal facial expressions and head movements in interview videos explained 91% and 84% of variance in self-reported honest and deceptive impression management, outperforming human interviewers' correlations with the same self-reports.