RefRoute: Learning to Search, Construct, and Verify References for Video Generation

Video generators can condition on images, video clips, and audios, yet satisfying a video generation request often depends on choosing the right information and control signal before generation. We present RefRoute, a generator-agnostic agent that learns to search for external evidence or construct multimodal references, and then assigns each asset a role in a generator-ready request. Its reference routes cover retrieved media, 2D event timing, 3D scene and camera path, reconstructed body motion, and video depth. We train a reference-routing policy from 12k teacher trajectories; we also specify two group-relative reinforcement-learning stages for route and video feedback. RefRoute-Bench evaluates 600 requests across five request categories for different knowledge gaps and reference routes. In the evaluation, RefRoute with MiniMax H3 Base show apparent improvements compared with the generator alone, with the largest gain on video retrieval.