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Beating AI Express (Insight): Luo Fuli, head of Xiaomi’s MiMo project, further explained the current round of reinforcement learning after the release of MiMo-V2.6. She noted that she previously worked on DeepSeek R1, and in her view, the research innovations and engineering challenges behind MiMo-V2.6 exceed those of R1. She also clarified why MiMo uses both MixRL and MOPD: MixRL trains verifiable tasks such as code, general agents, vision, and cybersecurity all within a single round of reinforcement learning. MOPD, meanwhile, handles long, hard-to-verify, or subjectively rewarded tasks by training them separately first, then integrating their capabilities back into the main model. Tasks like games and 3D take too long to run at once and are difficult to auto-assess for correctness. If grouped with code and other tasks in the same RL round, they would significantly slow down training. As a result, MiMo trains these tasks separately and integrates their capabilities into the main model via MOPD.
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