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20212026
most citedNatural Attack for Pre-trained Models of Code

163 citations · 493 across the 35 of their papers we have counts for

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Showing 2023Show all

15 papers · 1 filter

cs.SE2023★ 3 cited

Gotcha! This Model Uses My Code! Evaluating Membership Leakage Risks in Code Models

Zhou Yang, Zhipeng Zhao, Chenyu Wang +4

Given large-scale source code datasets available in open-source projects and advanced large language models, recent code models have been proposed to address a series of critical s…

cs.SE2023★ 2 cited

CCBERT: Self-Supervised Code Change Representation Learning

Xin Zhou, Bowen Xu, DongGyun Han +3

Numerous code changes are made by developers in their daily work, and a superior representation of code changes is desired for effective code change analysis. Recently, Hoang et al…

cs.SE2023★ 32 cited

Greening Large Language Models of Code

Jieke Shi, Zhou Yang, Hong Jin Kang +3

Large language models of code have shown remarkable effectiveness across various software engineering tasks. Despite the availability of many cloud services built upon these powerf…

cs.SE2023★ 119 cited

Large Language Models for Software Engineering: A Systematic Literature Review

Xinyi Hou, Yanjie Zhao, Yue Liu +7

Large Language Models (LLMs) have significantly impacted numerous domains, including Software Engineering (SE). Many recent publications have explored LLMs applied to various SE ta…

cs.SE2023★ 41 cited

Unveiling Memorization in Code Models

Zhou Yang, Zhipeng Zhao, Chenyu Wang +4

The availability of large-scale datasets, advanced architectures, and powerful computational resources have led to effective code models that automate diverse software engineering…

cs.CL2023

Source Code Data Augmentation for Deep Learning: A Survey

Terry Yue Zhuo, Zhou Yang, Zhensu Sun +5

The increasingly popular adoption of deep learning models in many critical source code tasks motivates the development of data augmentation (DA) techniques to enhance training data…

cs.SE2023

Synthesizing Speech Test Cases with Text-to-Speech? An Empirical Study on the False Alarms in Automated Speech Recognition Testing

Julia Kaiwen Lau, Kelvin Kai Wen Kong, Julian Hao Yong +7

Recent studies have proposed the use of Text-To-Speech (TTS) systems to automatically synthesise speech test cases on a scale and uncover a large number of failures in ASR systems.…

cs.SE2023

APISENS- Sentiment Scoring Tool for APIs with Crowd-Knowledge

Kisub Kim, Ferdian Thung, Ting Zhang +4

Utilizing pre-existing software artifacts, such as libraries and Application Programming Interfaces (APIs), is crucial for software development efficiency. However, the abundance o…

cs.SE2023

APIHarvest: Harvesting API Information from Various Online Sources

Ferdian Thung, Kisub Kim, Ting Zhang +4

Using APIs to develop software applications is the norm. APIs help developers to build applications faster as they do not need to reinvent the wheel. It is therefore important for…

cs.SE2023★ 2 cited

What Do Users Ask in Open-Source AI Repositories? An Empirical Study of GitHub Issues

Zhou Yang, Chenyu Wang, Jieke Shi +5

Artificial Intelligence systems, which benefit from the availability of large-scale datasets and increasing computational power, have become effective solutions to various critical…

cs.SE2023★ 2 cited

NICHE: A Curated Dataset of Engineered Machine Learning Projects in Python

Ratnadira Widyasari, Zhou Yang, Ferdian Thung +8

Machine learning (ML) has gained much attention and been incorporated into our daily lives. While there are numerous publicly available ML projects on open source platforms such as…

cs.SE2023★ 2 cited

Representation Learning for Stack Overflow Posts: How Far are We?

Junda He, Zhou Xin, Bowen Xu +6

The tremendous success of Stack Overflow has accumulated an extensive corpus of software engineering knowledge, thus motivating researchers to propose various solutions for analyzi…

eess.AS2023★ 1 cited

ASDF: A Differential Testing Framework for Automatic Speech Recognition Systems

Daniel Hao Xian Yuen, Andrew Yong Chen Pang, Zhou Yang +3

Recent years have witnessed wider adoption of Automated Speech Recognition (ASR) techniques in various domains. Consequently, evaluating and enhancing the quality of ASR systems is…

cs.SE2023★ 4 cited

Prioritizing Speech Test Cases

Zhou Yang, Jieke Shi, Muhammad Hilmi Asyrofi +4

With the wide adoption of automated speech recognition (ASR) systems, it is increasingly important to test and improve ASR systems. However, collecting and executing speech test ca…

cs.CR2023★ 16 cited

Stealthy Backdoor Attack for Code Models

Zhou Yang, Bowen Xu, Jie M. Zhang +4

Code models, such as CodeBERT and CodeT5, offer general-purpose representations of code and play a vital role in supporting downstream automated software engineering tasks. Most re…