Author

Sagnik Mukherjee

University of Illinois, Urbana Champaign

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#machine learning Preprint Sep 2026

Understanding LLM Parameter Update Sparsity through the Lens of Fisher

Recent studies have observed that parameter changes during language-model post-training can be concentrated in a small subset of coordinates. This phenomenon has been reported in reinforcement learning, on-policy distillation, and supervised fine-tuning on near-policy data. Its recurrence across different post-training...

Yu-Fan Zhang, Sagnik Mukherjee, Hao Peng · 0 citations

Jul 2026

ISO: An RLVR-Native Optimization Stack

Reinforcement learning with verifiable rewards (RLVR) is rapidly advancing the reasoning capabilities of language models, yet the optimization layer that converts reward feedback into weight-space updates remains poorly understood. Building on our prior analysis (Zhu et al., 2025), we study this missing layer through t...

Hanqing Zhu, Wenyan Cong, Zhizhou Sha et al. · arXiv.org · 0 citations