Jingyi Wang

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 57

Top Topics

Copyright Protection

Neural Classifier

Probabilistic Model

Top Venues

IEEE Trans. Software Eng.

ACM Trans. Softw. Eng. Methodol.

Publications

Shunkai Zhu, Jingyi Wang, Jun Sun, Jie Yang, Xingwei Lin, Tian Wang, Liyi Zhang, Peng Cheng
Better Pay Attention Whilst Fuzzing. IEEE Trans. Software Eng. 50 (2) (2024)
Zichen Wang, Jingyi Wang, Fu Song, Kun Wang, Hongyi Pu, Peng Cheng
K-RAPID: A Formal Executable Semantics of the RAPID Robot Programming Language. CPSS@AsiaCCS (2024)
Kun Wang, Christopher M. Poskitt, Yang Sun, Jun Sun, Jingyi Wang, Peng Cheng, Jiming Chen
μDrive: User-Controlled Autonomous Driving. CoRR (2024)
Zhe Zhao, Guangke Chen, Tong Liu, Taishan Li, Fu Song, Jingyi Wang, Jun Sun
Attack as Detection: Using Adversarial Attack Methods to Detect Abnormal Examples. ACM Trans. Softw. Eng. Methodol. 33 (3) (2024)
Xiaohan Yuan, Jinfeng Li, Dongxia Wang, Yuefeng Chen, Xiaofeng Mao, Longtao Huang, Hui Xue, Wenhai Wang, Kui Ren, Jingyi Wang
S-Eval: Automatic and Adaptive Test Generation for Benchmarking Safety Evaluation of Large Language Models. CoRR (2024)
Xiaokun Luan, Xiyue Zhang, Jingyi Wang, Meng Sun
Protecting Deep Learning Model Copyrights with Adversarial Example-Free Reuse Detection. CoRR (2024)
Kun Wang, Jingyi Wang, Christopher M. Poskitt, Xiangxiang Chen, Jun Sun, Peng Cheng
K-ST: A Formal Executable Semantics of the Structured Text Language for PLCs. IEEE Trans. Software Eng. 49 (10) (2023)
Xiaoxia Liu, Jingyi Wang, Jun Sun, Xiaohan Yuan, Guoliang Dong, Peng Di, Wenhai Wang, Dongxia Wang
Prompting Frameworks for Large Language Models: A Survey. CoRR (2023)
Huizhong Guo, Jinfeng Li, Jingyi Wang, Xiangyu Liu, Dongxia Wang, Zehong Hu, Rong Zhang, Hui Xue
FairRec: Fairness Testing for Deep Recommender Systems. CoRR (2023)
Jialuo Chen, Youcheng Sun, Jingyi Wang, Peng Cheng, Xingjun Ma
DEEPJUDGE: A Testing Framework for Copyright Protection of Deep Learning Models. ICSE Companion (2023)
Jialuo Chen, Jingyi Wang, Xingjun Ma, Youcheng Sun, Jun Sun, Peixin Zhang, Peng Cheng
QuoTe: Quality-oriented Testing for Deep Learning Systems. ACM Trans. Softw. Eng. Methodol. 32 (5) (2023)
Mengdi Zhang, Jun Sun, Jingyi Wang, Bing Sun
TestSGD: Interpretable Testing of Neural Networks against Subtle Group Discrimination. ACM Trans. Softw. Eng. Methodol. 32 (6) (2023)
Yifan Jia, Christopher M. Poskitt, Peixin Zhang, Jingyi Wang, Jun Sun, Sudipta Chattopadhyay
Boosting Adversarial Training in Safety-Critical Systems Through Boundary Data Selection. IEEE Robotics Autom. Lett. 8 (12) (2023)
Huizhong Guo, Jinfeng Li, Jingyi Wang, Xiangyu Liu, Dongxia Wang, Zehong Hu, Rong Zhang, Hui Xue
FairRec: Fairness Testing for Deep Recommender Systems. ISSTA (2023)
Yangyang Geng, Yuqi Chen, Rongkuan Ma, Qiang Wei, Jie Pan, Jingyi Wang, Peng Cheng, Qingxian Wang
Defending Cyber-Physical Systems Through Reverse-Engineering-Based Memory Sanity Check. IEEE Internet Things J. 10 (10) (2023)
Guoliang Dong, Jingyi Wang, Jun Sun, Sudipta Chattopadhyay, Xinyu Wang, Ting Dai, Jie Shi, Jin Song Dong
Repairing Adversarial Texts Through Perturbation. TASE (2022)
Jialuo Chen, Jingyi Wang, Tinglan Peng, Youcheng Sun, Peng Cheng, Shouling Ji, Xingjun Ma, Bo Li, Dawn Song
Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models. IEEE Symposium on Security and Privacy (2022)
Mengdi Zhang, Jun Sun, Jingyi Wang, Bing Sun
TESTSGD: Interpretable Testing of Neural Networks Against Subtle Group Discrimination. CoRR (2022)
Haibin Zheng, Zhiqing Chen, Tianyu Du, Xuhong Zhang, Yao Cheng, Shouling Ji, Jingyi Wang, Yue Yu, Jinyin Chen
NeuronFair: Interpretable White-Box Fairness Testing through Biased Neuron Identification. ICSE (2022)
Kun Wang, Jingyi Wang, Christopher M. Poskitt, Xiangxiang Chen, Jun Sun, Peng Cheng
K-ST: A Formal Executable Semantics of PLC Structured Text Language. CoRR (2022)
Peixin Zhang, Jingyi Wang, Jun Sun, Xinyu Wang, Guoliang Dong, Xingen Wang, Ting Dai, Jin Song Dong
Automatic Fairness Testing of Neural Classifiers Through Adversarial Sampling. IEEE Trans. Software Eng. 48 (9) (2022)
Rongkuan Ma, Qiang Wei, Jingyi Wang, Shunkai Zhu, Shouling Ji, Peng Cheng, Yan Jia, Qingxian Wang
Towards Comprehensively Understanding the Run-time Security of Programmable Logic Controllers: A 3-year Empirical Study. CoRR (2022)
Xiangshan Gao, Xingjun Ma, Jingyi Wang, Youcheng Sun, Bo Li, Shouling Ji, Peng Cheng, Jiming Chen
VeriFi: Towards Verifiable Federated Unlearning. CoRR (2022)
Mengdi Zhang, Jun Sun, Jingyi Wang
Which neural network makes more explainable decisions? An approach towards measuring explainability. Autom. Softw. Eng. 29 (2) (2022)
Yifan Jia, Jingyi Wang, Christopher M. Poskitt, Sudipta Chattopadhyay, Jun Sun, Yuqi Chen
Adversarial attacks and mitigation for anomaly detectors of cyber-physical systems. Int. J. Crit. Infrastructure Prot. 34 (2021)
Zhe Zhao, Guangke Chen, Jingyi Wang, Yiwei Yang, Fu Song, Jun Sun
Attack as defense: characterizing adversarial examples using robustness. ISSTA (2021)
Jingyi Wang, Jialuo Chen, Youcheng Sun, Xingjun Ma, Dongxia Wang, Jun Sun, Peng Cheng
RobOT: Robustness-Oriented Testing for Deep Learning Systems. CoRR (2021)
Jingyi Wang, Jun Sun, Shengchao Qin, Cyrille Jégourel
Automatically 'Verifying' Discrete-Time Complex Systems through Learning, Abstraction and Refinement. IEEE Trans. Software Eng. 47 (1) (2021)
Pengfei Yang, Renjue Li, Jianlin Li, Cheng-Chao Huang, Jingyi Wang, Jun Sun, Bai Xue, Lijun Zhang
Improving Neural Network Verification through Spurious Region Guided Refinement. TACAS (1) (2021)
Jingyi Wang, Jialuo Chen, Youcheng Sun, Xingjun Ma, Dongxia Wang, Jun Sun, Peng Cheng
RobOT: Robustness-Oriented Testing for Deep Learning Systems. ICSE (2021)
Peixin Zhang, Jingyi Wang, Jun Sun, Xinyu Wang, Guoliang Dong, Xingen Wang, Ting Dai, Jin Song Dong
Automatic Fairness Testing of Neural Classifiers through Adversarial Sampling. CoRR (2021)
Zhe Zhao, Guangke Chen, Jingyi Wang, Yiwei Yang, Fu Song, Jun Sun
Attack as Defense: Characterizing Adversarial Examples using Robustness. CoRR (2021)
Yifan Jia, Jingyi Wang, Christopher M. Poskitt, Sudipta Chattopadhyay, Jun Sun, Yuqi Chen
Adversarial Attacks and Mitigation for Anomaly Detectors of Cyber-Physical Systems. CoRR (2021)
Yizhen Dong, Peixin Zhang, Jingyi Wang, Shuang Liu, Jun Sun, Jianye Hao, Xinyu Wang, Li Wang, Jin Song Dong, Ting Dai
An Empirical Study on Correlation between Coverage and Robustness for Deep Neural Networks. ICECCS (2020)
Guoliang Dong, Jun Sun, Jingyi Wang, Xinyu Wang, Ting Dai
Towards Repairing Neural Networks Correctly. CoRR (2020)
Peixin Zhang, Jingyi Wang, Jun Sun, Guoliang Dong, Xinyu Wang, Xingen Wang, Jin Song Dong, Ting Dai
White-box fairness testing through adversarial sampling. ICSE (2020)
Guoliang Dong, Jingyi Wang, Jun Sun, Yang Zhang, Xinyu Wang, Ting Dai, Jin Song Dong, Xingen Wang
Towards Interpreting Recurrent Neural Networks through Probabilistic Abstraction. ASE (2020)
Pengfei Yang, Renjue Li, Jianlin Li, Cheng-Chao Huang, Jingyi Wang, Jun Sun, Bai Xue, Lijun Zhang
Improving Neural Network Verification through Spurious Region Guided Refinement. CoRR (2020)
Guoliang Dong, Jingyi Wang, Jun Sun, Yang Zhang, Xinyu Wang, Ting Dai, Jin Song Dong
Analyzing Recurrent Neural Network by Probabilistic Abstraction. CoRR (2019)
Yizhen Dong, Peixin Zhang, Jingyi Wang, Shuang Liu, Jun Sun, Jianye Hao, Xinyu Wang, Li Wang, Jin Song Dong, Dai Ting
There is Limited Correlation between Coverage and Robustness for Deep Neural Networks. CoRR (2019)
Jingyi Wang, Guoliang Dong, Jun Sun, Xinyu Wang, Peixin Zhang
Adversarial sample detection for deep neural network through model mutation testing. ICSE (2019)
Jingyi Wang, Jun Sun, Peixin Zhang, Xinyu Wang
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing. CoRR (2018)
Cyrille Jégourel, Jingyi Wang, Jun Sun
Importance Sampling of Interval Markov Chains. DSN (2018)
Xinyu Wang, Jun Sun, Zhenbang Chen, Peixin Zhang, Jingyi Wang, Yun Lin
Towards optimal concolic testing. ICSE (2018)
Jingyi Wang, Jun Sun, Yifan Jia, Shengchao Qin, Zhiwu Xu
Towards 'Verifying' a Water Treatment System. FM (2018)
Jingyi Wang, Jun Sun, Qixia Yuan, Jun Pang
Learning probabilistic models for model checking: an evolutionary approach and an empirical study. Int. J. Softw. Tools Technol. Transf. 20 (6) (2018)
Jingyi Wang, Guoliang Dong, Jun Sun, Xinyu Wang, Peixin Zhang
Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing. CoRR (2018)
Jingyi Wang, Xiaohong Chen, Jun Sun, Shengchao Qin
Improving Probability Estimation Through Active Probabilistic Model Learning. ICFEM (2017)
Long H. Pham, Jun Sun, Lyly Tran Thi, Jingyi Wang, Xin Peng
Learning Likely Invariants to Explain Why a Program Fails. ICECCS (2017)
Jingyi Wang, Jun Sun, Qixia Yuan, Jun Pang
Should We Learn Probabilistic Models for Model Checking? A New Approach and An Empirical Study. FASE (2017)
Jingyi Wang, Jun Sun, Yifan Jia
Toward 'verifying' a Water Treatment System. CoRR (2017)
Manman Chen, Tian Huat Tan, Jun Sun, Jingyi Wang, Yang Liu, Jing Sun, Jin Song Dong
Service Adaptation with Probabilistic Partial Models. ICFEM (2016)
Pingfan Kong, Yi Li, Xiaohong Chen, Jun Sun, Meng Sun, Jingyi Wang
Towards Concolic Testing for Hybrid Systems. CoRR (2016)
Jingyi Wang, Jun Sun, Qixia Yuan, Jun Pang
Should We Learn Probabilistic Models for Model Checking? A New Approach and An Empirical Study. CoRR (2016)
Pingfan Kong, Yi Li, Xiaohong Chen, Jun Sun, Meng Sun, Jingyi Wang
Towards Concolic Testing for Hybrid Systems. FM (2016)
Jun Sun, Long H. Pham, Lyly Tran Thi, Jingyi Wang, Xin Peng
Learning Likely Invariants to Explain Why a Program Fails. CoRR (2016)
Jingyi Wang, Jun Sun, Shengchao Qin
Verifying Complex Systems Probabilistically through Learning, Abstraction and Refinement. CoRR (2016)