Large language models (LLMs) can generate syntactically valid fuzzing seeds, but existing methods mainly focus on model adaptation and prompt design rather than static characteristics of target programs. This paper presents PCCFuzz, which uses source-visible program information to guide LLM-based initial seed generatio...
Jia-Hao Zhang· 2026 6th International Confe...· 0 citations
Tool calling, invoking external tools on demand, is central to agentic LLMs, yet the mechanism that decides whether a model calls a tool or responds directly remains poorly understood. Agentic prompts are long and heavily scaffolded, combining role instructions, tool schemas, format templates, and the user's request ac...
X. Gong, Ting-Xu Han, Jia-Hao Zhang et al.· 0 citations
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