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LALMs can achieve superior emotional comparison accuracy with only 5% of the training data typically required by conventional methods.
Agent systems leveraging iterative tool orchestration and cross-modal analysis significantly outperform single models in audio reasoning, highlighting a promising path toward explainable audio intelligence.