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Highway networks. arXiv preprint arXiv:1505.00387."},{"key":"e_1_3_2_1_77_1","unstructured":"Visual Studio. 2006. x86 Assembly Guide. \t\t\t\t  Visual Studio. 2006. x86 Assembly Guide."},{"key":"e_1_3_2_1_78_1","doi-asserted-by":"publisher","DOI":"10.1145\/2892208.2892235"},{"key":"e_1_3_2_1_79_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33017055"},{"key":"e_1_3_2_1_80_1","doi-asserted-by":"crossref","unstructured":"Alexey Svyatkovskiy Todd Mytkowicz Negar Ghorbani Sarah Fakhoury Elizabeth Dinella Christian Bird Neel Sundaresan and Shuvendu Lahiri. 2021. MergeBERT: Program Merge Conflict Resolution via Neural Transformers. arXiv preprint arXiv:2109.00084. \t\t\t\t  Alexey Svyatkovskiy Todd Mytkowicz Negar Ghorbani Sarah Fakhoury Elizabeth Dinella Christian Bird Neel Sundaresan and Shuvendu Lahiri. 2021. 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