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SongCraft, a latent flow matching based model trained for both generation and fine-grained editing, is presented, showing that a single model can support editing of lyrics, vocal melody, beats, and singer identity and the trade-off between reconstruction quality and editability is studied.
Forget complex architectures and task-specific designs: VLMs are already native 3D learners with the right training recipe.
