Search Results for author: Cuiyun Gao

Found 17 papers, 5 papers with code

Generating Tips from Song Reviews: A New Dataset and Framework

no code implementations14 May 2022 Jingya Zang, Cuiyun Gao, Yupan Chen, Ruifeng Xu, Lanjun Zhou, Xuan Wang

However, reviews of music songs are generally long in length and most of them are non-informative for users.

HINNPerf: Hierarchical Interaction Neural Network for Performance Prediction of Configurable Systems

no code implementations8 Apr 2022 Jiezhu Cheng, Cuiyun Gao, Zibin Zheng

Due to the complex interactions among multiple options and the high cost of performance measurement under a huge configuration space, it is challenging to study how different configurations influence the system performance.

Graph Partner Neural Networks for Semi-Supervised Learning on Graphs

no code implementations18 Oct 2021 Langzhang Liang, Cuiyun Gao, Shiyi Chen, Shishi Duan, Yu Pan, Junjin Zheng, Lei Wang, Zenglin Xu

Graph Convolutional Networks (GCNs) are powerful for processing graph-structured data and have achieved state-of-the-art performance in several tasks such as node classification, link prediction, and graph classification.

Classification Graph Classification +2

Code Structure Guided Transformer for Source Code Summarization

no code implementations19 Apr 2021 Shuzheng Gao, Cuiyun Gao, Yulan He, Jichuan Zeng, Lun Yiu Nie, Xin Xia

While Transformer-based approaches achieve promising performance, they do not explicitly incorporate the code structure information which is important for capturing code semantics.

Code Summarization Inductive Bias +1

Emerging App Issue Identification via Online Joint Sentiment-Topic Tracing

no code implementations23 Aug 2020 Cuiyun Gao, Jichuan Zeng, Zhiyuan Wen, David Lo, Xin Xia, Irwin King, Michael R. Lyu

Experiments on popular apps from Google Play and Apple's App Store demonstrate the effectiveness of MERIT in identifying emerging app issues, improving the state-of-the-art method by 22. 3% in terms of F1-score.

CoreGen: Contextualized Code Representation Learning for Commit Message Generation

1 code implementation14 Jul 2020 Lun Yiu Nie, Cuiyun Gao, Zhicong Zhong, Wai Lam, Yang Liu, Zenglin Xu

In this paper, we propose a novel Contextualized code representation learning strategy for commit message Generation (CoreGen).

Representation Learning Text Generation

On the Replicability and Reproducibility of Deep Learning in Software Engineering

no code implementations25 Jun 2020 Chao Liu, Cuiyun Gao, Xin Xia, David Lo, John Grundy, Xiaohu Yang

Experimental results show the importance of replicability and reproducibility, where the reported performance of a DL model could not be replicated for an unstable optimization process.

Feature Engineering

Why an Android App is Classified as Malware? Towards Malware Classification Interpretation

1 code implementation24 Apr 2020 Bozhi Wu, Sen Chen, Cuiyun Gao, Lingling Fan, Yang Liu, Weiping Wen, Michael R. Lyu

In this paper, to fill this gap, we propose a novel and interpretable ML-based approach (named XMal) to classify malware with high accuracy and explain the classification result meanwhile.

Android Malware Detection Classification +2

Automating App Review Response Generation

1 code implementation10 Feb 2020 Cuiyun Gao, Jichuan Zeng, Xin Xia, David Lo, Michael R. Lyu, Irwin King

Previous studies showed that replying to a user review usually has a positive effect on the rating that is given by the user to the app.

Response Generation

What Changed Your Mind: The Roles of Dynamic Topics and Discourse in Argumentation Process

no code implementations10 Feb 2020 Jichuan Zeng, Jing Li, Yulan He, Cuiyun Gao, Michael R. Lyu, Irwin King

In our world with full of uncertainty, debates and argumentation contribute to the progress of science and society.

CORE: Automating Review Recommendation for Code Changes

no code implementations20 Dec 2019 JingKai Siow, Cuiyun Gao, Lingling Fan, Sen Chen, Yang Liu

The hinge of accurate code review suggestion is to learn good representations for both code changes and reviews.

ATOM: Commit Message Generation Based on Abstract Syntax Tree and Hybrid Ranking

no code implementations6 Dec 2019 Shangqing Liu, Cuiyun Gao, Sen Chen, Lun Yiu Nie, Yang Liu

Moreover, although generation models have the advantages of synthesizing commit messages for new code changes, they are not easy to bridge the semantic gap between code and natural languages which could be mitigated by retrieval models.

Software Engineering

An Online Topic Modeling Framework with Topics Automatically Labeled

no code implementations WS 2019 Fenglei Jin, Cuiyun Gao, Michael R. Lyu

In this paper, we propose a novel online topic tracking framework, named IEDL, for tracking the topic changes related to deep learning techniques on Stack Exchange and automatically interpreting each identified topic.

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