Simin Chen
Simin Chen
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May 2023 -- One paper has been accepted to ACL 2023.
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May 12, 2023
3 min read
Publication
February 2023 -- Two papers have been accepted to CVPR 2023.
We are pleased to announce that our paper on efficiency backdoor attacks and transferability attacks for human face recognition systems has been accepted for presentation at the prestigious Conference on Computer Vision and Pattern Recognition (CVPR) in 2023.
Feb 27, 2023
3 min read
Publication
January 2023 -- One paper is accepted to ISSTA 2023.
Our paper, DyCL, is accepted to ISSTA 2023. DyCL is a automatic tool that rewrites the dynamic neural networks for supporting existing DL compilers.
Jan 16, 2023
3 min read
Publication
April 2022 -- One paper is accepted to ASE 2022.
Our paper, DeepPerform, is accepted to ASE 2022. DeepPerform is designed to test the performance robustness of adaptive neural networks.
Aug 30, 2022
3 min read
Publication
June 2022 -- One paper is accepted to ESEC/FSE 2022.
Our paper, NMTSloth, is accepted to ESEC/FSE 2022. NMTSloth is designed to test the performance degradation bugs in neural machine translation systems. We show NMTSloth can generate generate inputs that increase neural machine translation systems computational consumption upto 3153%.
Jun 14, 2022
3 min read
Publication
April 2022 -- One paper is accepted to IJCAI 2022.
Our paper, NNReverse, is accepted to IJCAI 2022. NNReverse is an automatic approach for reversing DNNs from AI programs.
Apr 22, 2022
3 min read
Publication
April 2022 -- Serve as a student volunteer in ICSE 2022
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Apr 6, 2022
3 min read
Publication
Program Committee Member -- MSR2023, CVPR 2023, AAAI 2023, WACV 2022, ECCV 2022
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Apr 6, 2022
Publication
Sub-Reviewer -- ICSE 2023, ICST 2023, ASE 2022, ICST 2022, ICSE 2021
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Apr 6, 2022
Publication
March 2022 -- One paper is accepted to CVPR 2022.
Our paper, NICGSlowDown, is accepted to CVPR 2022. To the best of our knowledge, NICGSlowDown is the first work to evaluate the efficiency robustness of neural caption generation models.
Mar 3, 2022
3 min read
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