MusTBENCH evaluates temporal grounding in large audio-language models via five expert-validated tasks, and MusT improves performance through encoder adaptation, LLM adaptation, supervised fine-tuning, and RL optimization.
10 Edith Law, Kris West, Michael I Mandel, Mert Bay, and J Stephen Downie
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MusTBENCH: Benchmarking and Advancing Temporal Grounding in Music LLMs
MusTBENCH evaluates temporal grounding in large audio-language models via five expert-validated tasks, and MusT improves performance through encoder adaptation, LLM adaptation, supervised fine-tuning, and RL optimization.