Position: The Hidden Costs and Measurement Gaps of Reinforcement Learning with Verifiable Rewards 事件

Position: The Hidden Costs and Measurement Gaps of Reinforcement Learning with Verifiable Rewards arXiv:2509.21882v3 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is a practical, scalable way to improve large language models on math, code, and other structured tasks. However, we argue that many headline RLVR gains are not yet well validated because reports often conflate policy improvement with three confounds: (i) budget mismatch between RLVR and