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Token likelihood changes can mislead researchers into overestimating the value of intermediate actions in self-distillation, with experiments showing near-chance performance in scoring effectiveness.
LiteMVS achieves superior depth estimation and 3D reconstruction by merging monocular insights with multi-view geometric reasoning, all while keeping inference costs low.
PathScale-R1 outperforms existing models in multi-scale reasoning, revealing that integrating diverse magnification levels can significantly enhance diagnostic accuracy.
