Yueh-Se Li

Breaking the Ceiling of the LLM Community by Treating Token Generation as a Classification for Ensembling

Ensembling multiple models has always been an effective approach to push the limits of existing performance and is widely used in classification tasks by simply averaging the classification probability vectors from multiple classifiers to achieve better accuracy. However, in the thriving open-source…