LRCC: Generalizing Low-Rank Compression with Conditional Computation
arXiv:2610.08858v1 Announce Type: new Abstract: Low-rank compression reduces the cost of pretrained language models by replacing linear transformations with low-rank factorizations. However, conventional methods use a fixed rank allocation during inference, assigning the same amount of compute rega…
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- 2026-10-08 04:00 · arXiv cs.CL
LRCC: Generalizing Low-Rank Compression with Conditional Computation