Xiaosha Li

WHEN NOISE LOWERS THE LOSS: RETHINKING LIKELIHOOD-BASED EVALUATION IN MUSIC LARGE LANGUAGE MODELS

The rise of music large language models (LLMs) demands robust methods of evaluating output quality, especially in distinguishing high-quality compositions from "garbage music". Curiously, we observe that the standard cross-entropy loss -- a core training metric -- often decrease when models encounte…