Search Results for author: Zhenchang Xing

Found 8 papers, 2 papers with code

Generating Informative CVE Description From ExploitDB Posts by Extractive Summarization

no code implementations5 Jan 2021 Jiamou Sun, Zhenchang Xing, Hao Guo, Deheng Ye, Xiaohong Li, Xiwei Xu, Liming Zhu

The extracted aspects from an ExploitDB post are then composed into a CVE description according to the suggested CVE description templates, which is must-provided information for requesting new CVEs.

Extractive Summarization Text Summarization

Brain-inspired Search Engine Assistant based on Knowledge Graph

no code implementations25 Dec 2020 Xuejiao Zhao, Huanhuan Chen, Zhenchang Xing, Chunyan Miao

However, when a query is complex, developers need to repeatedly refine the search keywords and open a large number of web pages to find and summarize answers.

Decision Making

Holistic Combination of Structural and Textual Code Information for Context based API Recommendation

no code implementations15 Oct 2020 Chi Chen, Xin Peng, Zhenchang Xing, Jun Sun, Xin Wang, Yifan Zhao, Wenyun Zhao

APIRec-CST is a deep learning model that combines the API usage with the text information in the source code based on an API Context Graph Network and a Code Token Network that simultaneously learn structural and textual features for API recommendation.

Object Detection for Graphical User Interface: Old Fashioned or Deep Learning or a Combination?

1 code implementation12 Aug 2020 Jieshan Chen, Mulong Xie, Zhenchang Xing, Chunyang Chen, Xiwei Xu, Liming Zhu, Guoqiang Li

We conduct the first large-scale empirical study of seven representative GUI element detection methods on over 50k GUI images to understand the capabilities, limitations and effective designs of these methods.

Code Generation Object Detection

Searching Scientific Literature for Answers on COVID-19 Questions

no code implementations6 Jul 2020 Vincent Nguyen, Maciek Rybinski, Sarvnaz Karimi, Zhenchang Xing

Finding answers related to a pandemic of a novel disease raises new challenges for information seeking and retrieval, as the new information becomes available gradually.

Information Seeking

Unblind Your Apps: Predicting Natural-Language Labels for Mobile GUI Components by Deep Learning

1 code implementation1 Mar 2020 Jieshan Chen, Chunyang Chen, Zhenchang Xing, Xiwei Xu, Liming Zhu, Guoqiang Li, Jinshui Wang

However, the prerequisite of using screen readers is that developers have to add natural-language labels to the image-based components when they are developing the app.

ANU-CSIRO at MEDIQA 2019: Question Answering Using Deep Contextual Knowledge

no code implementations WS 2019 Vincent Nguyen, Sarvnaz Karimi, Zhenchang Xing

We report on our system for textual inference and question entailment in the medical domain for the ACL BioNLP 2019 Shared Task, MEDIQA.

Natural Language Inference Question Answering

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