Reasoning traces generated by large language models (LLMs) provide interpretability by exposing the factors that purportedly support their predictions. Such interpretability is important because model decisions may rely on spurious factors, and it can help practitioners identify such reliance and respond appropriately....
Jia-Lai Wang, Jun-Chen Lu, Song-Tao Yang et al.· Proceedings of the 41st IEEE...· 0 citations
Decompilation remains foundational for binary analysis, yet conventional tools prioritize human readability over compilation success and test-validated runtime consistency. While recent large language model approaches attempt refining decompiled pseudocode, they often introduce semantic hallucinations. Operating static...
Yu-Xin Cui, Ze-Yu Gao, Si-Liang Qin et al.· Proceedings of the 41st IEEE...· 0 citations
Software composition analysis (SCA) aims to identify third-party dependencies in programs, which plays a critical role in ensuring software supply chain security. Existing approaches largely follow a rule-based paradigm: they first compute function-level similarities, then aggregate these results using handcrafted heur...
Pei-Hong Li, Cheng Li, Yu-Chen Gu et al.· Proceedings of the ACM on So...· 0 citations
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