Correlation-Aware Structured Pruning for Large Language Models
arXiv:2609.22131v1 Announce Type: new Abstract: Structured pruning is a promising approach for reducing the substantial inference costs of Large Language Models (LLMs) while maintaining hardware efficiency. Many existing methods assess the importance of prunable units (e.g., channels or heads) in i…
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- 2026-09-22 04:00 · arXiv cs.CL
Correlation-Aware Structured Pruning for Large Language Models