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Eigenpruning
April 5, 2024, 4:41 a.m. | Tom\'as Vergara-Browne, \'Alvaro Soto, Akiko Aizawa
cs.LG updates on arXiv.org arxiv.org
Abstract: We introduce eigenpruning, a method that removes singular values from weight matrices in an LLM to improve its performance in a particular task. This method is inspired by interpretability methods designed to automatically find subnetworks of a model which solve a specific task. In our tests, the pruned model outperforms the original model by a large margin, while only requiring minimal computation to prune the weight matrices. In the case of a small synthetic task …
abstract arxiv cs.ai cs.lg interpretability llm performance singular solve tests type values
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