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Training LLMs and other models is feasible and effective using a mix of human-annotated and ML-generated labels, bypassing the bottleneck of full human annotation.
Clinical behavioral screening can reach a 0.59 F1 without ever exposing raw video or audio of minors, but moving from coarse screening to granular psychometric item prediction hits an immediate performance wall across current multimodal architectures.
Real-time speech conversion for dysarthric individuals can now achieve unprecedented intelligibility and naturalness, transforming professional communication.
Query probabilities can stabilize and improve mean estimation accuracy by balancing uncertainty with a constant probability, revealing a surprising optimal weight configuration.