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...
محفوظ في:
المؤلفون الرئيسيون: | BUI, Duy Quoc Nghi, YU, Yijun |
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التنسيق: | text |
اللغة: | English |
منشور في: |
Institutional Knowledge at Singapore Management University
2022
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الموضوعات: | |
الوصول للمادة أونلاين: | https://ink.library.smu.edu.sg/sis_research/10117 https://ink.library.smu.edu.sg/context/sis_research/article/11117/viewcontent/RobustModelsCode_pv.pdf |
الوسوم: |
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