Author

Shiwei Liu

UT Austin

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Jul 2026

SLORR: Simple and Efficient In-Training Low-Rank Regularization

SLORR, a simple, stateless, and architecture-preserving framework for in-training low-rank regularization, instantiated with two main variants based on the Hoyer sparsity metric and the nuclear norm, is introduced.

David González-Martínez, Shiwei Liu · arXiv.org · 0 citations