AINeutralarXiv – CS AI · 6h ago6/10
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On the Implicit Reward Overfitting and the Low-rank Dynamics in RLVR
A new research paper identifies implicit reward overfitting in Reinforcement Learning with Verifiable Rewards (RLVR), revealing that model improvements concentrate in rank-1 components while potentially sacrificing broader knowledge retention. The findings suggest RLVR optimizes singular spectrum distributions rather than general reasoning, with implications for improving AI training paradigms and continual learning approaches.