3 papers
cs.CL2024
Aquila2 Technical Report
Bo-Wen Zhang, Liangdong Wang, Jijie Li +6
This paper introduces the Aquila2 series, which comprises a wide range of bilingual models with parameter sizes of 7, 34, and 70 billion. These models are trained based on an innov…
cs.CL2024
AquilaMoE: Efficient Training for MoE Models with Scale-Up and Scale-Out Strategies
Bo-Wen Zhang, Liangdong Wang, Ye Yuan +24
In recent years, with the rapid application of large language models across various fields, the scale of these models has gradually increased, and the resources required for their…
cs.CL2024
CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning
Zheqi He, Xinya Wu, Pengfei Zhou +5
Multi-modal large language models(MLLMs) have achieved remarkable progress and demonstrated powerful knowledge comprehension and reasoning abilities. However, the mastery of domain…