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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| Main Authors: | , |
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| 格式: | text |
| 語言: | English |
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Institutional Knowledge at Singapore Management University
2022
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| 在線閱讀: | 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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