16 citations · 17 across the 3 of their papers we have counts for
5 papers · 1 filter
FoundaBench: Evaluating Chinese Fundamental Knowledge Capabilities of Large Language Models
Wei Li, Ren Ma, Jiang Wu +7
In the burgeoning field of large language models (LLMs), the assessment of fundamental knowledge remains a critical challenge, particularly for models tailored to Chinese language…
InternLM2 Technical Report
Zheng Cai, Maosong Cao, Haojiong Chen +97
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI). However, replicating such advan…
Benchmarking Chinese Commonsense Reasoning of LLMs: From Chinese-Specifics to Reasoning-Memorization Correlations
Jiaxing Sun, Weiquan Huang, Jiang Wu +5
We introduce CHARM, the first benchmark for comprehensively and in-depth evaluating the commonsense reasoning ability of large language models (LLMs) in Chinese, which covers both…
MiChao-HuaFen 1.0: A Specialized Pre-trained Corpus Dataset for Domain-specific Large Models
Yidong Liu, FuKai Shang, Fang Wang +5
With the advancement of deep learning technologies, general-purpose large models such as GPT-4 have demonstrated exceptional capabilities across various domains. Nevertheless, ther…
WanJuan: A Comprehensive Multimodal Dataset for Advancing English and Chinese Large Models
Conghui He, Zhenjiang Jin, Chao Xu +6
The rise in popularity of ChatGPT and GPT-4 has significantly accelerated the development of large models, leading to the creation of numerous impressive large language models(LLMs…