3 papers
cs.CL2025
E-Pruner: Towards Efficient, Economical, and Effective Layer Pruning for Large Language Models
Tao Yuan, Haoli Bai, Yinfei Pan +5
With the increasing size of large language models, layer pruning has gained increased attention as a hardware-friendly approach for model compression. However, existing layer pruni…
cs.CL2025
Pangu Light: Weight Re-Initialization for Pruning and Accelerating LLMs
Hanting Chen, Jiarui Qin, Jialong Guo +15
Large Language Models (LLMs) deliver state-of-the-art capabilities across numerous tasks, but their immense size and inference costs pose significant computational challenges for p…
cs.CL2025
A Simple Linear Patch Revives Layer-Pruned Large Language Models
Xinrui Chen, Haoli Bai, Tao Yuan +7
Layer pruning has emerged as a widely used technique for compressing large language models (LLMs). However, existing layer pruning approaches often incur substantial performance de…