AI RESEARCH

Baton: Explicit Semantic Blueprints for Joint Video-Audio Generation

arXiv CS.CV

ArXi:2605.25195v2 Announce Type: replace Current open-source diffusion models struggle to generate stable and synchronized audio-visual content, particularly in scenarios demanding complex semantic reasoning. The root cause is that existing methods rely on coarse text embeddings from off-the-shelf encoders to guide audio-video denoising, which discards fine-grained semantics and, critically, lacks a shared long-horizon plan, leading to uncoordinated denoising trajectories and fragile cross-modal alignment. We propose Baton, the first framework that.