TokenWave.AI

A closer look at YuE2: from prompt roulette to editable AI music. YuE2 is a 3.58B-parameter open-weight music model that writes an editable melody-and-chord score before rendering a complete song with vocals and accompaniment. We see YuE2 as a step toward a new paradigm for AI music: explicit musical planning, with a score that creators and agents can inspect and revise before it becomes audio. The paper tests whether that planning helps. Using the same model checkpoint, 49.3% of expert judgments favored symbolic planning versus 34.6% without it; the rest were ties. TokenWave supplied most of the project’s synthetic training data under license, as acknowledged in the paper. We’re glad to have contributed alongside HKUST, M-A-P, and the wider research team to this direction: making musical structure explicit, editable, and part of generation itself. What does this make possible? 🎼 Edit the composition. Change the melody or harmony, then render a new performance. The exact vocals and sound may vary between versions. 🎙️ Reimagine a song. Use a transcribed melody to create a new interpretation in a different style, without cover-specific fine-tuning. 🤖 Collaborate with an agent. An external language-model agent translates musical feedback into score, style, or lyric revisions. YuE2 generates the audio. Under the hood, a unified AR–NAR Mixture-of-Transformers connects scores to audio through semantic tokens and flow-matched acoustic latents. MERT2 and SheetSage2 provide semantic and symbolic training supervision. Demos and editable scores: map-yue2.github.io/ Paper: arxiv.org/abs/2609.33757 Code: github.com/multimodal-art-pr…