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cs.SE2026
On the Lexical Superstition of Large Language Models for Code Comprehension: Re-evaluation on Code of Low Lexical Quality
Xin Shen, San-Zhuo Xi, Yali Du +1
Recent advances in large language models (LLMs) have made them widely used for code-related tasks. Identifier names are statistically informative in naturally occurring code, but t…
cs.AI2026
CIT-CAD: Constraint Intent Tree-based CAD Code Generation and Verification
Yali Du, Hui Sun, San-Zhuo Xi +1
Natural-language Computer-Aided Design (CAD) code generation aims to turn design intent into executable and editable parametric programs. Large language models (LLMs) make this goa…
cs.LG2026
ACES: Who Tests the Tests? Leave-One-Out AUC Consistency for Code Generation
Hui Sun, Yun-Ji Zhang, Zheng Xie +4
Selecting LLM-generated code candidates using LLM-generated tests is challenging because the tests themselves may be incorrect. Existing methods either treat all tests equally or r…