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Real-time emotion predictions can be made more reliable by selectively invoking multimodal reasoning only when necessary, improving accuracy without sacrificing speed.
Achieving over 99% performance retention while significantly accelerating large recommendation models by intelligently merging experts based on functional similarity.
Achieving an impressive hierarchical F1 score of 81.25% through innovative multi-branch modeling and KNN post-processing reveals new potential in audio classification tasks.