no code implementations • 30 Mar 2024 • Yuji Cao, Huan Zhao, Yuheng Cheng, Ting Shu, Guolong Liu, Gaoqi Liang, Junhua Zhao, Yun Li
With extensive pre-trained knowledge and high-level general capabilities, large language models (LLMs) emerge as a promising avenue to augment reinforcement learning (RL) in aspects such as multi-task learning, sample efficiency, and task planning.
1 code implementation • 28 Feb 2024 • Sirui Hong, Yizhang Lin, Bang Liu, Bangbang Liu, Binhao Wu, Danyang Li, Jiaqi Chen, Jiayi Zhang, Jinlin Wang, Li Zhang, Lingyao Zhang, Min Yang, Mingchen Zhuge, Taicheng Guo, Tuo Zhou, Wei Tao, Wenyi Wang, Xiangru Tang, Xiangtao Lu, Xiawu Zheng, Xinbing Liang, Yaying Fei, Yuheng Cheng, Zongze Xu, Chenglin Wu
Large Language Model (LLM)-based agents have demonstrated remarkable effectiveness.
1 code implementation • 7 Jan 2024 • Yuheng Cheng, Ceyao Zhang, Zhengwen Zhang, Xiangrui Meng, Sirui Hong, Wenhao Li, ZiHao Wang, Zekai Wang, Feng Yin, Junhua Zhao, Xiuqiang He
Intelligent agents stand out as a potential path toward artificial general intelligence (AGI).
1 code implementation • 1 Aug 2023 • Sirui Hong, Mingchen Zhuge, Jonathan Chen, Xiawu Zheng, Yuheng Cheng, Ceyao Zhang, Jinlin Wang, Zili Wang, Steven Ka Shing Yau, Zijuan Lin, Liyang Zhou, Chenyu Ran, Lingfeng Xiao, Chenglin Wu, Jürgen Schmidhuber
Remarkable progress has been made on automated problem solving through societies of agents based on large language models (LLMs).
Ranked #7 on Code Generation on HumanEval