1 code implementation • EMNLP 2020 • Jiaqi Guo, Qian Liu, Jian-Guang Lou, Zhenwen Li, Xueqing Liu, Tao Xie, Ting Liu
Thus, the impact of meaning representation on semantic parsing is less understood.
no code implementations • 27 Nov 2022 • Xueqing Liu, Tao Tu, Paul Sajda
Simultaneous EEG-fMRI is a multi-modal neuroimaging technique that provides complementary spatial and temporal resolution.
1 code implementation • COLING 2022 • Guanqun Yang, Mirazul Haque, Qiaochu Song, Wei Yang, Xueqing Liu
Our experiments show that TestAug has three advantages over the existing work on behavioral testing: (1) TestAug can find more bugs than existing work; (2) The test cases in TestAug are more diverse; and (3) TestAug largely saves the manual efforts in creating the test suites.
1 code implementation • 14 Aug 2021 • Guanqun Yang, Shay Dineen, Zhipeng Lin, Xueqing Liu
In this work, for the first time, we propose to investigate this problem where only a small number of labeled training samples are available.
1 code implementation • ACL 2021 • Xueqing Liu, Chi Wang
We find that using the same time budget, HPO often fails to outperform grid search due to two reasons: insufficient time budget and overfitting.
no code implementations • 5 Oct 2020 • Xueqing Liu, Linbi Hong, Paul Sajda
Simultaneous EEG-fMRI is a multi-modal neuroimaging technique that provides complementary spatial and temporal resolution for inferring a latent source space of neural activity.
no code implementations • 5 Jul 2020 • Yongqian Xiao, Xinglong Zhang, Xin Xu, Xueqing Liu, Jiahang Liu
Furthermore, a data-driven model predictive controller with the learned Koopman model is designed for path tracking control of autonomous vehicles.
no code implementations • 1 Jun 2020 • Xueqing Liu, Paul Sajda
Many imaging technologies rely on tomographic reconstruction, which requires solving a multidimensional inverse problem given a finite number of projections.
no code implementations • 15 Jan 2020 • Haoran Sun, Xueqing Liu, Xinyang Feng, Chen Liu, Nanyan Zhu, Sabrina J. Gjerswold-Selleck, Hong-Jian Wei, Pavan S. Upadhyayula, Angeliki Mela, Cheng-Chia Wu, Peter D. Canoll, Andrew F. Laine, J. Thomas Vaughan, Scott A. Small, Jia Guo
Together, these studies validate our hypothesis that a deep learning approach can potentially replace the need for GBCAs in brain MRI.
no code implementations • 13 Mar 2014 • Chi Wang, Xueqing Liu, Yanglei Song, Jiawei Han
Automated generation of high-quality topical hierarchies for a text collection is a dream problem in knowledge engineering with many valuable applications.