Tandem Reinforcement Learning with Verifiable Rewards
arXiv:2606.28166v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has significantly improved the reasoning capability of large language models, reaching expert or even superhuman performance in domains such as competition math. However, whether weaker agents and humans can actually harness this capability is far less certain, with RLVR documented to drift reasoning toward idiosyncratic patterns such as poor readability and language mixing. Tandem training is a...
arXiv cs.AI
·Difan Jiao, Raghav Singhal, Robert West, Ashton Anderson
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