Score-aware training uses alignment scores to route low-quality segments into high-noise regimes as implicit regularizers, enabling a 450M model to rank competitively in a text-to-music challenge with limited data.
When bad data leads to good models,
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Making the Most of Limited Data: Score-Aware Training for Text-to-Music Generation
Score-aware training uses alignment scores to route low-quality segments into high-noise regimes as implicit regularizers, enabling a 450M model to rank competitively in a text-to-music challenge with limited data.