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2025 ICML ICML 2025

An Efficient Pruner for Large Language Model with Theoretical Guarantee

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

Authors

Canhong Wen, Yihong Zuo, Wenliang Pan

Topics

Machine Learning > Optimization & Theory > Optimization Machine Learning > Application Areas > Efficient Computing Artificial Intelligence > Core AI > Large Language Models

Keywords

convergence theoretical guarantee iterative hard thresholding large language model pruning llama-7b
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