1 citations · 1 across the 10 of their papers we have counts for
6 papers · 1 filter
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…
Evaluating Language Models on Cross-Language Code Functional Equivalence
Hui Sun, Anderson Uchôa, Rohit Gheyi +1
Background: Large Language Models (LLMs) have demonstrated strong performance across a variety of code-understanding tasks, leading many to believe that they can reason about progr…
Exploring Pass-Rate Reward in Reinforcement Learning for Code Generation
Xin-Ye Li, Ren-Biao Liu, Yun-Ji Zhang +3
Reinforcement learning (RL) from unit-test feedback has become a standard post-training recipe for improving large language models (LLMs) on code generation. However, the pass-all-…
SpecRL: Reinforcement Learning with Test-Based Completeness Rewards for Formal Specification Synthesis
Zhechong Huang, Zhao Zhang, Zeyu Sun +2
Specification synthesis asks a model to generate specifications and auxiliary annotations for an existing program. In modern software verification projects, specification accuracy…
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…
Design-Specification Tiling for ICL-based CAD Code Generation
Yali Du, San-Zhuo Xi, Hui Sun +1
Large language models~(LLMs) have demonstrated remarkable capabilities in code generation, yet their performance remains limited on domain-specific tasks such as Computer-Aided Des…