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arxiv_cs_lg · Jul 9, 2026 · paper

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

arxiv.orgJul 9, 2026
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In brief

Low-rank factorization is widely used to compress neural networks, but modern models are often not naturally amenable to aggressive factorization without significant accuracy loss. Existing training-time low-rank regu...

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

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