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Taozhaowen Taozhaowen

1 accepted papers

2025

Accelerating Dense LLMs via L0-regularized Mixture-of-Experts

ACL 2025short

Large language models (LLMs) achieve strong performance but suffer from slow and costly inference. Existing acceleration methods often lead to noticeable performance degradation, while Mixture-of-Experts (MoE) models require extensive computational resources. In this paper, we propose L0-MoE, a ligh…