activity
20182023
most citedDeepASL: Enabling Ubiquitous and Non-Intrusive Word and Sentence-Level Sign Language Translation

108 citations · 139 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SP2023★ 1 cited

ETP: Learning Transferable ECG Representations via ECG-Text Pre-training

Che Liu, Zhongwei Wan, Sibo Cheng +2

In the domain of cardiovascular healthcare, the Electrocardiogram (ECG) serves as a critical, non-invasive diagnostic tool. Although recent strides in self-supervised learning (SSL…

cs.CL2023★ 30 cited

Med-UniC: Unifying Cross-Lingual Medical Vision-Language Pre-Training by Diminishing Bias

Zhongwei Wan, Che Liu, Mi Zhang +6

The scarcity of data presents a critical obstacle to the efficacy of medical visionlanguage pre-training (VLP). A potential solution lies in the combination of datasets from variou…

cs.CL2022

Automatically Generating Counterfactuals for Relation Classification

Mi Zhang, Tieyun Qian, Ting Zhang

The goal of relation classification (RC) is to extract the semantic relations between/among entities in the text. As a fundamental task in natural language processing, it is crucia…

cs.CL2019

How Sequence-to-Sequence Models Perceive Language Styles?

Ruozi Huang, Mi Zhang, Xudong Pan +1

Style is ubiquitous in our daily language uses, while what is language style to learning machines? In this paper, by exploiting the second-order statistics of semantic vectors of d…

stat.ML2018

Theoretical Analysis of Image-to-Image Translation with Adversarial Learning

Xudong Pan, Mi Zhang, Daizong Ding

Recently, a unified model for image-to-image translation tasks within adversarial learning framework has aroused widespread research interests in computer vision practitioners. The…

cs.CV2018★ 108 cited

DeepASL: Enabling Ubiquitous and Non-Intrusive Word and Sentence-Level Sign Language Translation

Biyi Fang, Jillian Co, Mi Zhang

There is an undeniable communication barrier between deaf people and people with normal hearing ability. Although innovations in sign language translation technology aim to tear do…