Author

Hao Zhu

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#artificial intelligence Preprint Sep 2026

Self-Spec Verifiable Code Generation

Large language models (LLMs) may generate unreliable code on corner cases missed by testing, while formal verification can provide machine-checkable guarantees. Recently, researchers have proposed several benchmarks to evaluate the capabilities of LLMs in generating formally verifiable code, where LLMs need to formulat...

Jia-Ru Qian, Yihong Dong, Yong-Ming Li et al. · 0 citations

Preprint Aug 2026

PRAXIS: Graph-Grounded Tacit Knowledge for Domain Code Generation

PRAXIS is a framework that enables agents to systematically extract, represent, and reuse tacit knowledge for domain code generation and outperforms state-of-the-art agents equipped with powerful agentic search capabilities, as well as experience-based and skill-based methods.

Xue Jiang, Tianyue H. Zhang, Ling-Wei Wu et al. · 0 citations