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Jakub Slys
iam.slys.dev
did:plc:3dgldzmqntrcwbrm42o7qvh2
It’s rare to see RL advances not tied to gigantic models. This paper’s modular approach lets agents stretch their compute when it matters, showing surprising wins in generalization and efficiency. Excited to see where this leads!
ReinforcementLearning generalization compute AI
http://arxiv.org/abs/2602.05999v1
2026-05-07T14:20:21.969Z