Towards robust models of code via energy-based learning on auxiliary datasets

Existing approaches to improving the robustness of source code models concentrate on recognizing adversarial samples rather than valid samples that fall outside of a given distribution, which we refer to as out-of-distribution (OOD) samples. To this end, we propose to use an auxiliary dataset (out-o...

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Bibliographic Details
Main Authors: BUI, Duy Quoc Nghi, YU, Yijun
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2022
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Online Access:https://ink.library.smu.edu.sg/sis_research/10117
https://ink.library.smu.edu.sg/context/sis_research/article/11117/viewcontent/RobustModelsCode_pv.pdf
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Institution: Singapore Management University
Language: English