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ISO: An RLVR-Native Optimization Stack

5 upvotes · 21 JUL 2026 · Hanqing Zhu, Wenyan Cong, Zhizhou Sha et al.

This paper develops a new optimization framework called Isospectral Optimization (ISO) that improves the performance of language models trained using reinforcement learning with verifiable rewards (RLVR) by reusing the base model's weight spectra while adapting the input and output singular frames. Practitioners might care about this because it could lead to faster and more accurate training of large language models.

reinforcement learningverifiable rewardssingular value decompositionoptimization frameworksweight spectraframe changes