MIMO-V2.6: SCALING REINFORCEMENT LEARNING TOWARDS SELF-IMPROVEMENT

Summary from the TLDR AI newsletter

Reinforcement learning is the central training paradigm for advancing large foundation models towards self-improvement. The Mimo-V2.6 series is an omni-model family that pushes the frontier of model intelligence by scaling RL compute. Training was kept stable at scale by freezing the MoE router and establishing a multi-layer defense against reward hacking. The training dynamics, RL environments, and RL framework have been open-sourced to facilitate reproduction and further research on scaled RL and model self-improvement.