Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.
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