Author

Xiao Shi

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#artificial intelligence Preprint Sep 2026

Per-Matrix Optimality Is Not Enough: Three-Level Optimization for Low-Rank LLM Compression

Per-matrix singular value decomposition (SVD) truncation is Eckart-Young optimal in the whitened Frobenius norm, but errors from independently compressed matrices compound through the block's nonlinear forward pass. Inspired in part by hierarchical variational optimization in quantum many-body methods, we introduce a t...

Hui-Cheng Zhang, Xi-Yao Feng, Ze-Tong Li et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Towards Evolving Context Parameterization for Large Language Models

Context parameterization enables large language models (LLMs) to internalize contexts into reusable model parameters, avoiding repeated processing across subsequent queries. However, existing methods typically assume static contexts and lack explicit mechanisms for distinguishing validity states under continual updates...

Xiao Shi, Zhe-Rui Li, Yi-Ming Jiang et al. · 0 citations