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Automated data curation and imbalance-aware training strategies significantly enhance LALMs' performance on culturally diverse folk music, yet deep musical understanding remains elusive.
Reward-based fine-tuning of a discrete diffusion model significantly enhances synthesizer inversion performance, outperforming traditional methods in audio matching tasks.
