4 citations · 13 across the 30 of their papers we have counts for
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cs.LG2023
PERP: Rethinking the Prune-Retrain Paradigm in the Era of LLMs
Max Zimmer, Megi Andoni, Christoph Spiegel +1
Neural Networks can be effectively compressed through pruning, significantly reducing storage and compute demands while maintaining predictive performance. Simple yet effective met…
cs.LG2023★ 3 cited
Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging
Max Zimmer, Christoph Spiegel, Sebastian Pokutta
Neural networks can be significantly compressed by pruning, yielding sparse models with reduced storage and computational demands while preserving predictive performance. Model sou…