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Transforming vector mapping into a language-based task unlocks unprecedented flexibility and generalization in remote sensing applications.
Overcome the limitations of existing semi-supervised segmentation methods by learning structural consensus across samples, achieving more generalizable pancreas segmentation under sparse supervision.
Recommendation systems can now systematically debias engagement signals across user, content, and model dimensions using a lightweight, in-model approach, leading to more accurate value models and stable ecosystem dynamics.
