arXiv:2607. 17526v1 Announce Type: cross Abstract: Zero-shot text-guided editing of real-world music recordings requires balancing semantic modification with faithful preservation of the original musical structure.
Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.
Zero-shot text-guided editing of real-world music recordings requires balancing semantic modification with faithful preservation of the original musical structure. Although recent diffusion transformers trained with rectified flow have achieved remarkable success in text-to-music generation, extending them to edit existing recordings remains challenging because editing requires accurate deterministic inversion, reliable structural preservation, and numerically stable integration throughout the inversion and generation processes.
arXiv:2606. 20101v3 Announce Type: replace-cross Abstract: Audio editing aims to modify specific content in an existing audio clip according to a text instruction or description while preserving the remaining acoustic content.
arXiv:2606. 20101v1 Announce Type: cross Abstract: Audio editing aims to modify specific content in an existing audio clip according to a natural language instruction while preserving the remaining acoustic content.
arXiv:2607. 11124v1 Announce Type: cross Abstract: Music creation is fundamentally a process of revision.
arXiv:2606. 22726v2 Announce Type: replace Abstract: Choreographic motion generation poses unique challenges for AI, demanding precise semantic control over complex, temporally structured, and expressive full-body dynamics.
arXiv:2606. 01703v1 Announce Type: cross Abstract: We address the challenge of generating high-fidelity, long-form soundtracks that remain coherent across scene transitions.