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Anticipatory Music Transformer
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(crfm.stanford.edu)
3 points
tarr11
2y ago
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Rochus
2y ago
The paper was submitted in June 2023. The results sound promising. The approach also seems interesting because apparently they use a different approach than the usual NLP embeddings to encode the training data.
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