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cs.LG2026
Wrong Votes, Right Gradients: Why Majority-Vote Rewards Track Verifiable RL
Dylan P. Wilson, Chengsong Huang, Jiaxin Huang
Reinforcement learning with self-generated labels, such as majority vote over a model's own samples, often recovers most of the gain of training with verifiable rewards. This is pu…
cs.LG2024
Adjusted Overfitting Regression
Dylan Wilson
In this paper, I will introduce a new form of regression, that can adjust overfitting and underfitting through, "distance-based regression." Overfitting often results in finding fa…