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Training physics-informed neural networks with a unified priority framework can dramatically improve convergence and accuracy by respecting the physical information flow.
Forget training separate models for every preference – this method lets you steer a single LLM across the Pareto frontier of multiple objectives, all on one GPU.
By explicitly modeling tooth relationships, TCATSeg achieves state-of-the-art accuracy in 3D dental model segmentation, even in challenging pre-orthodontic cases.
