3 citations · 6 across the 8 of their papers we have counts for
3 papers · 2 filters
Sigma-MoE-Tiny Technical Report
Qingguo Hu, Zhenghao Lin, Ziyue Yang +12
Mixture-of-Experts (MoE) has emerged as a promising paradigm for foundation models due to its efficient and powerful scalability. In this work, we present Sigma-MoE-Tiny, an MoE la…
Training Matryoshka Mixture-of-Experts for Elastic Inference-Time Expert Utilization
Yaoxiang Wang, Qingguo Hu, Yucheng Ding +6
Mixture-of-Experts (MoE) has emerged as a promising paradigm for efficiently scaling large language models without a proportional increase in computational cost. However, the stand…
Detecting Manipulated Contents Using Knowledge-Grounded Inference
Mark Huasong Meng, Ruizhe Wang, Meng Xu +2
The detection of manipulated content, a prevalent form of fake news, has been widely studied in recent years. While existing solutions have been proven effective in fact-checking a…