MusTBENCH: Benchmarking and Advancing Temporal Grounding in Music LLMs 事件

MusTBENCH: Benchmarking and Advancing Temporal Grounding in Music LLMs arXiv:2605.29300v1 Announce Type: new Abstract: Recent Large Audio-Language Models (LALMs) have demonstrated promising abilities in understanding musical content. However, whether their responses are grounded in the correct temporal regions of the audio remains underexplored. This limitation is particularly critical for music understanding, where key information often occurs as temporally localized events, such as instrument