26 citations · 49 across the 10 of their papers we have counts for
5 papers · 1 filter
Densing Law of LLMs
Chaojun Xiao, Jie Cai, Weilin Zhao +7
Large Language Models (LLMs) have emerged as a milestone in artificial intelligence, and their performance can improve as the model size increases. However, this scaling brings gre…
DecorateLM: Data Engineering through Corpus Rating, Tagging, and Editing with Language Models
Ranchi Zhao, Zhen Leng Thai, Yifan Zhang +6
The performance of Large Language Models (LLMs) is substantially influenced by the pretraining corpus, which consists of vast quantities of unsupervised data processed by the model…
MiniCPM-V: A GPT-4V Level MLLM on Your Phone
Yuan Yao, Tianyu Yu, Ao Zhang +20
The recent surge of Multimodal Large Language Models (MLLMs) has fundamentally reshaped the landscape of AI research and industry, shedding light on a promising path toward the nex…
PyBench: Evaluating LLM Agent on various real-world coding tasks
Yaolun Zhang, Yinxu Pan, Yudong Wang +1
The LLM Agent, equipped with a code interpreter, is capable of automatically solving real-world coding tasks, such as data analysis and image editing. However, existing benchmarks…
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies
Shengding Hu, Yuge Tu, Xu Han +22
The burgeoning interest in developing Large Language Models (LLMs) with up to trillion parameters has been met with concerns regarding resource efficiency and practical expense, pa…