1 code implementation • 25 May 2023 • Xin Qin, Jindong Wang, Shuo Ma, Wang Lu, Yongchun Zhu, Xing Xie, Yiqiang Chen
With the constructed self-supervised learning task, DDLearn enlarges the data diversity and explores the latent activity properties.
no code implementations • ACL 2020 • Yi Huang, Junlan Feng, Min Hu, Xiaoting Wu, Xiaoyu Du, Shuo Ma
The state-of-the-art accuracy for DST is below 50{\%} for a multi-domain dialogue task.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Yi Huang, Junlan Feng, Shuo Ma, Xiaoyu Du, Xiaoting Wu
In this paper, we propose a meta-learning based semi-supervised explicit dialogue state tracker (SEDST) for neural dialogue generation, denoted as MEDST.
no code implementations • 15 Jun 2021 • Shuo Ma, Muhao Chen, Xingfei Yuan, Robert E. Skelton
Results show that the proposed CTS cable dome always has one prestress mode and is globally stable in its deployment trajectory.
no code implementations • 17 Oct 2021 • Shuo Ma, Muhao Chen, Robert E. Skelton
This paper presents the formulations of nonlinear and linearized statics, dynamics, and control for any clustered tensegrity system (CTS).
no code implementations • 8 Jun 2022 • Shuo Ma, Yiqian Chen, Muhao Chen, Robert E. Skelton
This paper presents the equilibrium and stiffness study of clustered tensegrity structures (CTS) considering pulley sizes.
no code implementations • 26 Jun 2022 • Shuo Ma, Kai Lu, Muhao Chen, Robert E. Skelton
This paper presents an analytical and experimental design and deployment control analysis of a hyperbolic paraboloid cable net based on clustering actuation strategies.
no code implementations • 16 Feb 2023 • Esteve Valls Mascaro, Shuo Ma, Hyemin Ahn, Dongheui Lee
In addition, our model is tested in conditions where the human motion is severely occluded, demonstrating its robustness in reconstructing and predicting 3D human motion in a highly noisy environment.