AgentCPM-Explore: Realizing Long-Horizon Deep Exploration for Edge-Scale Agents

2月 1, 2026·
Haotian Chen
Haotian Chen
,
Xin Cong
,
Shengda Fan
,
Yuyang Fu
,
Ziqin Gong
,
Yaxi Lu
,
Yishan Li
,
Boye Niu
,
Chengjun Pan
,
Zijun Song
,
Huadong Wang
,
Yesai Wu
,
Yueying Wu
,
Zihao Xie
,
Yukun Yan
,
Zhong Zhang
,
Yankai Lin
,
Zhiyuan Liu
,
Maosong Sun
· 0 分钟阅读时长
摘要
We develop a unified tool sandbox environment management framework with end-to-end agent RL training. The 4B-parameter agent achieves SOTA among same-scale models, surpassing GPT-5 and Claude-4.5-Sonnet on GAIA and HLE benchmarks.
类型
出版物
ArXiv Preprint 2026
publications
Haotian Chen
Authors
Assistant Researcher
Haotian Chen is an Assistant Researcher at the School of Artificial Intelligence, Shanghai Jiao Tong University, working with Prof. Junchi Yan at RethinkLab. His research goal is to understand and develop AI for automating tasks that require extensive time, effort, and creative thinking. He works on automating data-driven scientific research, contributing to both alleviating the burden on humans and revolutionizing human productivity. His research focuses on Autonomous Agents, Large Language Models, and AI4Research. He received his PhD in Data Science from Fudan University and completed postdoctoral research at Tsinghua University (THUNLP), where he worked with Prof. Zhiyuan Liu and Prof. Maosong Sun. He was also a research intern at Microsoft Research Asia, where the RD-Agent project he co-developed was featured in the Microsoft Build 2025 Global Keynote.