Diffusion as a unifying backbone for multimodal generation

Latent diffusion now drives both image synthesis and video creation. Continuous‑time distribution matching reduces diffusion steps to a few while retaining fidelity [1] . Segment‑wise video diffusion extends the same idea to image‑to‑video tasks, cutting inference cost [2] . The gap is conditioning: current models still lack native text or segmentation prompts, limiting end‑to‑end multimodal pipelines.

Modular expert routing and adaptive compute

UniPool replaces per‑layer mixtures of experts with a single shared pool and a pooling loss, shrinking the expert parameter budget without hurting performance [3] . NormRouter further stabilises routing decisions across layers.…