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R虏-MAD not only corrects misconceptions in multi-agent debates but also intelligently weighs agent contributions based on past performance, leading to more accurate outcomes.
Flow-based VLAs can now learn online without likelihoods or value networks, unlocking better generalization in complex embodied control tasks.
