AgentCPM-Explore: Realizing Long-Horizon Deep Exploration for Edge-Scale Agents
2月 1, 2026·
,,,,,,,,,,,,,,,,,,·
0 分钟阅读时长
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
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

Authors
Haotian Chen
(he/him)
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.