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Retaining critical information in robot locomotion can yield a 15% performance boost while simplifying the model's architecture.
MEGA-CL achieves over 75% accuracy in ADMET predictions, significantly outperforming existing models and showcasing its potential for accelerating drug discovery.
Vision-language models consistently fail to recognize missing object parts, even when external evidence contradicts their visual perceptions, highlighting a fundamental flaw in their design.
