1 code implementation • 24 May 2024 • Yuanchun Wang, Jifan Yu, Zijun Yao, Jing Zhang, Yuyang Xie, Shangqing Tu, Yiyang Fu, Youhe Feng, Jinkai Zhang, Jingyao Zhang, Bowen Huang, Yuanyao Li, Huihui Yuan, Lei Hou, Juanzi Li, Jie Tang
Applying large language models (LLMs) for academic API usage shows promise in reducing researchers' academic information seeking efforts.
no code implementations • 30 Mar 2022 • Fan Zhang, Deyuan Meng, Jingyao Zhang
Simulations for networked spacecraft are presented to show the global synchronization performances under different directed topologies.
no code implementations • 20 Mar 2022 • Deyuan Meng, Jingyao Zhang
Generally, the classic iterative learning control (ILC) methods focus on finding design conditions for repetitive systems to achieve the perfect tracking of any specified trajectory, whereas they ignore a fundamental problem of ILC: whether the specified trajectory is trackable, or equivalently, whether there exist some inputs for the repetitive systems under consideration to generate the specified trajectory?
1 code implementation • 29 Oct 2020 • Yuncheng Hua, Yuan-Fang Li, Guilin Qi, Wei Wu, Jingyao Zhang, Daiqing Qi
Our framework consists of a neural generator and a symbolic executor that, respectively, transforms a natural-language question into a sequence of primitive actions, and executes them over the knowledge base to compute the answer.