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Princigram achieves a new standard in scientific diagram generation, ensuring physical accuracy through a structured reasoning framework that traditional models lack.
Achieving consistent voxel spacing can dramatically improve medical image segmentation quality, leading to better diagnostic and surgical outcomes.
Ling-2.6 and Ring-2.6 achieve unprecedented efficiency in agentic intelligence, enabling instant responses and deep reasoning at trillion-parameter scale.
Current AI models for liver fibrosis staging can match expert radiologists in some settings, but real-world clinical deployment is still hampered by data heterogeneity and label imbalance.
Achieve expert-level bronchoscopic navigation without external sensors by having a world-model critic arbitrate between reactive and strategic AI agents.
EndoSERV enables accurate endoluminal robot navigation even without real-world pose labels, by cleverly transferring real image features to a virtual environment for training.
