Augmenting Large Audio-Language Models with Frame-Level Grounding for Fine-Grained Temporal Perception
Large Audio-Language Models (LALMs) have substantially advanced general audio understanding, yet they remain limited in fine-grained temporal perception, particularly in precise event localization. Existing approaches primarily post-train LALMs to predict event boundaries as timestamp tokens. However, this generative f...
Yan Shi, Yan Song, Jun-Hui Li et al.
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