1 code implementation • 26 Jan 2024 • Yuhui Li, Fangyun Wei, Chao Zhang, Hongyang Zhang
In this paper, we reconsider speculative sampling and derive two key observations.
1 code implementation • 13 Sep 2023 • Yuhui Li, Fangyun Wei, Jinjing Zhao, Chao Zhang, Hongyang Zhang
We discover that by integrating self-evaluation and rewind mechanisms, unaligned LLMs can directly produce responses consistent with human preferences via self-boosting.
no code implementations • 27 Jun 2023 • Yifan Zhang, Arnav Vaibhav Malawade, Xiaofang Zhang, Yuhui Li, DongHwan Seong, Mohammad Abdullah Al Faruque, Sitao Huang
Autonomous systems (AS) are systems that can adapt and change their behavior in response to unanticipated events and include systems such as aerial drones, autonomous vehicles, and ground/aquatic robots.
no code implementations • 16 Jun 2023 • Qiankun Zuo, Yanfei Zhu, Libin Lu, Zhi Yang, Yuhui Li, Ning Zhang
In this paper, a novel hierarchical structural-functional connectivity fusing (HSCF) model is proposed to construct brain structural-functional connectivity matrices and predict abnormal brain connections based on functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI).
1 code implementation • 26 Nov 2022 • Yuhui Li, Zejia Wu, Chao Zhang, Hongyang Zhang
In this work, we introduce the concepts of direct and indirect effects from causal inference to the domain generalization problem.
no code implementations • 8 Aug 2021 • Jun Li, Shimei Chen, Shangyuan Wang, Miao Lei, Xiaofang Dai, Chuangxue Liang, Kunyuan Xu, Shuxin Lin, Yuhui Li, Yuer Fan, Ting Zhong
We presented an optical system to perform imaging interested objects in complex scenes, like the creature easy see the interested prey in the hunt for complex environments.
1 code implementation • 28 Oct 2020 • Jun Ma, Yao Zhang, Song Gu, Cheng Zhu, Cheng Ge, Yichi Zhang, Xingle An, Congcong Wang, Qiyuan Wang, Xin Liu, Shucheng Cao, Qi Zhang, Shangqing Liu, Yunpeng Wang, Yuhui Li, Jian He, Xiaoping Yang
With the unprecedented developments in deep learning, automatic segmentation of main abdominal organs seems to be a solved problem as state-of-the-art (SOTA) methods have achieved comparable results with inter-rater variability on many benchmark datasets.