6 papers
AppCopilot: Toward General, Accurate, Long-Horizon, and Efficient Mobile Agent
Jingru Fan, Yufan Dang, Jingyao Wu +5
With the raid evolution of large language models and multimodal models, the mobile-agent landscape has proliferated without converging on the fundamental challenges. This paper ide…
MiniCPM4: Ultra-Efficient LLMs on End Devices
MiniCPM Team, Chaojun Xiao, Yuxuan Li +80
This paper introduces MiniCPM4, a highly efficient large language model (LLM) designed explicitly for end-side devices. We achieve this efficiency through systematic innovation in…
Tool Learning with Foundation Models
Yujia Qin, Shengding Hu, Yankai Lin +38
Humans possess an extraordinary ability to create and utilize tools, allowing them to overcome physical limitations and explore new frontiers. With the advent of foundation models,…
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…
ChatDev: Communicative Agents for Software Development
Chen Qian, Wei Liu, Hongzhang Liu +11
Software development is a complex task that necessitates cooperation among multiple members with diverse skills. Numerous studies used deep learning to improve specific phases in a…
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…