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Fangying Rong

1 accepted papers

2024

Pruning via Merging: Compressing LLMs via Manifold Alignment Based Layer Merging

EMNLP 2024main

While large language models (LLMs) excel in many domains, their complexity and scale challenge deployment in resource-limited environments. Current compression techniques, such as parameter pruning, often fail to effectively utilize the knowledge from pruned parameters. To address these challenges,…