Author

Kevin Frans

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#machine learning Preprint Nov 2026

Stabilizing On-Policy Targeted Guidance in Agentic Reinforcement Learning

Naive on-policy RL is often bottlenecked by the capabilities of the base model --- insufficient coverage can result in an inability to learn from certain rewards. At the same time, rewards in modern post-training systems often come from rich textual sources, e.g. judge models with a rubric of criteria. Can we utilize s...

Kevin Frans, Alexander M. Rush, Sergey Levine et al. · 0 citations

#machine learning Preprint Sep 2026

Long-Horizon Language Model Reinforcement Learning via Progressive Point Matching

It is shown that a simple and unbiased dense reward formulation, which is term progressive point matching, scales exponentially more efficiently to long-horizon tasks by rewarding partial progress on a segment level, both theoretically and empirically via synthetic environments.

Preston Fu, Kevin Frans, Oleh Rybkin et al. · 0 citations