Text Models Spot Evasion Better Than They Read Vocal Confidence
Models performed strongly on written signs of evasion but struggled more with vocal unconfidence, and speaker-level calibration helped only modestly.
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Subject
Machine learning, neural networks, language models, and computer vision.
Models performed strongly on written signs of evasion but struggled more with vocal unconfidence, and speaker-level calibration helped only modestly.
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A systematic review finds that most deep-learning brain MRI reconstruction studies did not compare image-fidelity scores with radiologist assessments on the same data, leaving key safety questions unanswered.
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A video AI method called Token-Budget Distillation retained strong benchmark scores after aggressive visual-token compression, although its training still depended on the uncompressed teacher model.
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Journal of Bangladesh Academy of Sciences, vol. 50, Supplement 1, p. 114, 20265 min read
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