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Achieving high-resolution cardiac simulations with a method that guarantees reduced super-resolution error through physics-based constraints and Koopman regularization.
Tactile-reactive policies can boost robotic manipulation success rates by over 30% through innovative data collection and a new Mixture-of-Transformers architecture.
Extracting action signals from 32,041 hours of human video enables CAIP to outperform leading vision encoders in robotic manipulation tasks by over 30%.
LLMs can slash compute costs by up to 67% on reasoning tasks with a new online calibration method that adapts to each input at test time.
A 3B parameter model now rivals models 10x its size in reasoning, alignment, and agentic tasks, challenging the assumption that bigger is always better.
