时隔十年，AI大牛署名新论文

TL;DR - NIO researchers introduced MM-Future, a world–action model that jointly simulates multiple paired driving actions and future scenes before selecting a trajectory. It improves planning benchmarks by modeling how each candidate action could change the environment, though compute cost and extreme-scenario robustness remain limitations.

• MM-Future generates multiple paired scene–action hypotheses with bidirectional interaction, rather than predicting trajectories and future scenes sequentially or producing only one joint outcome.
• Gaussian-mixture action noise, independent scene noise, and Best-of-Many supervision preserve diverse candidates; compact MM-Tokens reduce the cost of representing multi-camera, multi-frame futures.
• The model achieved 94.0 PDMS on NAVSIM-v1 and 91.5 EPDMS on NAVSIM-v2; ablations showed gains from additional modes, joint scene–action generation, and future-conditioned candidate scoring.
• Sampling 64 candidates took about 233 ms on one NVIDIA H800, while implicit scene representations, route completion, and extreme-scenario performance require further improvement.