Five semantic-segmentation networks trained on 18,000 intraoral photographs from 3,000 patients, combined by a weighted pixel-by-pixel vote. Seven classes: background, tooth, gum, tartar, cavity, ...
The supervised fine-tuning dataset used to train MLE-World-Qwen3.5-4B, checkpoint 6685, the execution world model used in the Qwen3.5-9B stage-policy experiments ...
Регрессия, не видевшая ни одного пикселя, почти догоняет двухпоточную сеть по QWK и обгоняет её по AUC. По снимкам модель на самом деле даёт QWK ...
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