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A scalar adjoint method slashes the computational cost of fine-tuning flow policies in RL, achieving state-of-the-art results on complex manipulation tasks.
Implicit coordination in decentralized multi-agent systems can be achieved without direct communication, leading to a 38% success rate in complex manipulation tasks.