4 citations · 17 across the 25 of their papers we have counts for
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cs.LG2024★ 1 cited
ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models
Xiang Meng, Kayhan Behdin, Haoyue Wang +1
The impressive performance of Large Language Models (LLMs) across various natural language processing tasks comes at the cost of vast computational resources and storage requiremen…
cs.CV2024★ 2 cited
OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization
Xiang Meng, Shibal Ibrahim, Kayhan Behdin +3
Structured pruning is a promising approach for reducing the inference costs of large vision and language models. By removing carefully chosen structures, e.g., neurons or attention…