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September 20, 2025

NotaGen: Advancing Musicality in Symbolic Music Generation with Large Language Model Training Paradigms

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NotaGen demonstrates superior generation quality through its unique training paradigms, especially with CLaMP-DPO.
In subjective A/B tests, NotaGen notably outperformed traditional baseline models against human compositions.
The model's architecture includes both pre-training on large music datasets and fine-tuning on classical compositions.
Advancements in symbolic music generation significantly elevate the perception of musical aesthetics.

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Symbolic music generation shows improved quality with NotaGen using pre-training and reinforcement learning methods, indicating enhanced musicality.

Wang et al. (2024) studied this question.

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Symbolic music generation shows improved quality with NotaGen using pre-training and reinforcement learning methods, indicating enhanced musicality.