Predicting Music Valence and Arousal via Textual and Multimodal In-Context Learning in Large Language Models
This work investigates the potential of in-context learning (ICL) with large language models to advance continuous valence and arousal prediction and suggests that training-free ICL offers an effective inference-time strategy for current language models to predict continuous music emotion.
Chia Dai, Chih-Pin Tan, Yi-Hsuan Yang
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