1 code implementation • EMNLP 2020 • Guangtao Zeng, Wenmian Yang, Zeqian Ju, Yue Yang, Sicheng Wang, Ruisi Zhang, Meng Zhou, Jiaqi Zeng, Xiangyu Dong, Ruoyu Zhang, Hongchao Fang, Penghui Zhu, Shu Chen, Pengtao Xie
We also study the transferability of models trained on MedDialog to low-resource medical dialogue generation tasks.
no code implementations • ECCV 2020 • Huikun Bi, Ruisi Zhang, Tianlu Mao, Zhigang Deng, Zhaoqi Wang
This work presents a novel First-person View based Trajectory predicting model (FvTraj) to estimate the future trajectories of pedestrians in a scene given their observed trajectories and the corresponding first-person view images.
no code implementations • 21 Sep 2022 • Ruisi Zhang, Seira Hidano, Farinaz Koushanfar
Our attacks faithfully reconstruct private texts included in training data with access to the target model.
no code implementations • 30 Nov 2021 • Ruisi Zhang, Youwei Liang, Sai Ashish Somayajula, Pengtao Xie
We introduce a training strategy called ``Differentiable Architecture Search with a Generative Model(DASGM)."
no code implementations • 16 Sep 2020 • Ruisi Zhang, Luntian Mou, Pengtao Xie
Based on these two ideas, we propose a TreeGAN model which consists of three modules: (1) a class hierarchy encoder (CHE) which takes the hierarchical structure of classes and their textual names as inputs and learns an embedding for each class; the embedding captures the hierarchical relationship among classes; (2) a conditional image generator (CIG) which takes the CHE-generated embedding of a class as input and generates a set of images belonging to this class; (3) a consistency checker which performs hierarchical classification on the generated images and checks whether the generated images are compatible with the class hierarchy; the consistency score is used to guide the CIG to generate hierarchy-compatible images.
1 code implementation • arXiv 2020 • Xuehai He, Shu Chen, Zeqian Ju, Xiangyu Dong, Hongchao Fang, Sicheng Wang, Yue Yang, Jiaqi Zeng, Ruisi Zhang, Ruoyu Zhang, Meng Zhou, Penghui Zhu, Pengtao Xie
Medical dialogue systems are promising in assisting in telemedicine to increase access to healthcare services, improve the quality of patient care, and reduce medical costs.