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Author

Jinlong Xu

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Book Open access Oct 2026

BanditFuzz: A Synergistic Differential Fuzzing Framework for Compilers

Compiler fuzzing is critical for ensuring the reliability of modern optimizing compilers. However, traditional generators and raw Large Language Model (LLM) outputs often yield syntactically invalid or low-value programs, incurring significant computational overhead. In this paper, we present BanditFuzz, an end-to-end...

Dong-Hui Li, Ying-Ying Li, Jin-Long Xu et al. · 0 citations
Open access Aug 2026

RL–LLMfuzzer: reinforcement learning–guided dual–model differential fuzzing for compiler testing

RL-LLMfuzzer, a reinforcement learning and LLM-based differential fuzzing framework that has successfully unearthed 28 officially confirmed vulnerabilities in GCC and LLVM/Clang, establishing a highly efficient and scalable paradigm for LLM-driven compiler validation.

Dong-Hui Li, Ying-Ying Li, Bo Zhao et al. · 0 citations

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