Zhuopeng Wang

C-GNN-PRUNE: A Unified Graph-Based Framework for Structure-Aware Pruning of Mixture-of-Experts Models

The Mixture-of-Experts (MoE) architecture has emerged as a promising paradigm for scaling large language models (LLMs) by activating only a sparse subset of experts per input. However, its massive parameter size remains a major obstacle to efficient deployment. Existing pruning methods often ignore