25 citations · 25 across the 3 of their papers we have counts for
3 papers
cs.LG2025
MC#: Mixture Compressor for Mixture-of-Experts Large Models
Wei Huang, Yue Liao, Yukang Chen +6
Mixture-of-Experts (MoE) effectively scales large language models (LLMs) and vision-language models (VLMs) by increasing capacity through sparse activation. However, preloading all…
cs.LG2024
Mixture Compressor for Mixture-of-Experts LLMs Gains More
Wei Huang, Yue Liao, Jianhui Liu +6
Mixture-of-Experts large language models (MoE-LLMs) marks a significant step forward of language models, however, they encounter two critical challenges in practice: 1) expert para…
cs.LG2024★ 25 cited
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Wei Huang, Yangdong Liu, Haotong Qin +5
Pretrained large language models (LLMs) exhibit exceptional general language processing capabilities but come with significant demands on memory and computational resources. As a p…