3 papers
cs.SE2026
Reducing Hallucinations in LLM-Generated Code via Semantic Triangulation
Yihan Dai, Sijie Liang, Haotian Xu +2
Large language models (LLMs) can generate executable code from natural language descriptions, but the resulting programs frequently contain bugs due to hallucinations. In the absen…
cs.SE2025
Statistical Independence Aware Caching for LLM Workflows
Yihan Dai, Dimitrios Stamatios Bouras, Haoxiang Jia +1
Large language models (LLMs) inference is both expensive and slow. Local caching of responses offers a practical solution to reduce the cost and latency of LLM queries. In research…
cs.SE2025
HoarePrompt: Structural Reasoning About Program Correctness in Natural Language
Dimitrios Stamatios Bouras, Yihan Dai, Tairan Wang +2
While software requirements are often expressed in natural language, verifying the correctness of a program against such requirements is a hard and underexplored problem. Large lan…