6 citations · 12 across the 9 of their papers we have counts for
6 papers · 1 filter
Multi-modal Semantic Understanding with Contrastive Cross-modal Feature Alignment
Ming Zhang, Ke Chang, Yunfang Wu
Multi-modal semantic understanding requires integrating information from different modalities to extract users' real intention behind words. Most previous work applies a dual-encod…
Focus-Driven Contrastive Learniang for Medical Question Summarization
Ming Zhang, Shuai Dou, Ziyang Wang +1
Automatic medical question summarization can significantly help the system to understand consumer health questions and retrieve correct answers. The Seq2Seq model based on maximum…
Question-type Driven Question Generation
Wenjie Zhou, Minghua Zhang, Yunfang Wu
Question generation is a challenging task which aims to ask a question based on an answer and relevant context. The existing works suffer from the mismatching between question type…
Multi-Task Learning with Language Modeling for Question Generation
Wenjie Zhou, Minghua Zhang, Yunfang Wu
This paper explores the task of answer-aware questions generation. Based on the attention-based pointer generator model, we propose to incorporate an auxiliary task of language mod…
Learning Universal Sentence Representations with Mean-Max Attention Autoencoder
Minghua Zhang, Yunfang Wu, Weikang Li +1
In order to learn universal sentence representations, previous methods focus on complex recurrent neural networks or supervised learning. In this paper, we propose a mean-max atten…
An Unsupervised Model with Attention Autoencoders for Question Retrieval
Minghua Zhang, Yunfang Wu
Question retrieval is a crucial subtask for community question answering. Previous research focus on supervised models which depend heavily on training data and manual feature engi…