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SymLM: Predicting Function Names in Stripped Binaries via Context-Sensitive Execution-Aware Code Embeddings., , , and . CCS, page 1631-1645. ACM, (2022)Exploiting Code Symmetries for Learning Program Semantics., , , , , , , and . ICML, OpenReview.net, (2024)DeepXplore: Automated Whitebox Testing of Deep Learning Systems., , , and . GetMobile, 22 (3): 36-38 (2018)DeepXplore: Automated Whitebox Testing of Deep Learning Systems., , , and . SOSP, page 1-18. ACM, (2017)Formal Security Analysis of Neural Networks using Symbolic Intervals., , , , and . USENIX Security Symposium, page 1599-1614. USENIX Association, (2018)XDA: Accurate, Robust Disassembly with Transfer Learning., , , , and . NDSS, The Internet Society, (2021)TRACED: Execution-aware Pre-training for Source Code., , , , , and . ICSE, page 36:1-36:12. ACM, (2024)DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars., , , and . CoRR, (2017)NEUZZ: Efficient Fuzzing with Neural Program Smoothing., , , , , and . IEEE Symposium on Security and Privacy, page 803-817. IEEE, (2019)SWE-bench: Can Language Models Resolve Real-World GitHub Issues?, , , , , , and . CoRR, (2023)