6 citations · 12 across the 9 of their papers we have counts for
9 papers
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…
CPS-MEBR: Click Feedback-Aware Web Page Summarization for Multi-Embedding-Based Retrieval
Wenbiao Li, Pan Tang, Zhengfan Wu +7
Embedding-based retrieval (EBR) is a technique to use embeddings to represent query and document, and then convert the retrieval problem into a nearest neighbor search problem in t…
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…
Light yield and field dependence measurement in PandaX-II dual-phase xenon detector
Zhou Huang, Abdusalam Abdukerim, Zihao Bo +76
The dual-phase xenon time projection chamber (TPC) is one of the most sensitive detector technology for dark matter direct search, where the energy deposition of incoming particle…
AGCM-3DLF: Accelerating Atmospheric General Circulation Model via 3D Parallelization and Leap-Format
Hang Cao, Liang Yuan, He Zhang +1
The Atmospheric General Circulation Model (AGCM) has been an important research tool in the study of climate change for decades. As the demand for high-resolution simulation is bec…
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…