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Fine-grained spatio-temporal reasoning in audio-language models can dramatically enhance the understanding of complex multi-event audio sequences.
Post-training with LoRA can boost accuracy in some models while hindering others, revealing the nuanced interplay between architecture and adaptation in audio-dependent tasks.
