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Alec Radford Jeff Wu Rewon Child David Luan Dario Amodei and Ilya Sutskever. 2019. Language Models are Unsupervised Multitask Learners."},{"key":"e_1_3_2_1_65_1","volume-title":"Liu","author":"Raffel Colin","year":"2019","unstructured":"Colin Raffel , Noam Shazeer , Adam Roberts , Katherine Lee , Sharan Narang , Michael Matena , Yanqi Zhou , Wei Li , and Peter J . Liu . 2019 . Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. CoRR , abs\/1910.10683 (2019), arXiv:1910.10683. arxiv:1910.10683 Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2019. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. 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In International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment. 255\u2013275 . Tielei Wang, Chengyu Song, and Wenke Lee. 2014. Diagnosis and emergency patch generation for integer overflow exploits. In International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment. 255\u2013275."},{"key":"e_1_3_2_1_73_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.685"},{"key":"e_1_3_2_1_74_1","unstructured":"Chunqiu Steven Xia Yuxiang Wei and Lingming Zhang. 2022. Practical Program Repair in the Era of Large Pre-trained Language Models. arXiv preprint arXiv:2210.14179. Chunqiu Steven Xia Yuxiang Wei and Lingming Zhang. 2022. 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