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cs.LG2026
RLVR landscapes for iterated multiplications can be benign: Insights from spin-glass theory
Noa Rubin, Zohar Ringel
Despite the importance of reinforcement learning with verifiable rewards (RLVR), the extent to which it can learn new reasoning capabilities remains debated. Here we study the opti…
cs.LG2025
Mitigating the Curse of Detail: Scaling Arguments for Feature Learning and Sample Complexity
Noa Rubin, Orit Davidovich, Zohar Ringel
Two pressing topics in the theory of deep learning are the interpretation of feature learning (FL) mechanisms and the determination of implicit bias of networks in the rich regime.…