3 papers
cs.CV2026
Omni-I2C: A Holistic Benchmark for High-Fidelity Image-to-Code Generation
Jiawei Zhou, Chi Zhang, Xiang Feng +6
We present Omni-I2C, a comprehensive benchmark designed to evaluate the capability of Large Multimodal Models (LMMs) in converting complex, structured digital graphics into executa…
cs.SE2026
Unseen-Codebases-Domain Data Synthesis and Training Based on Code Graphs
Guangsheng Ou, Qiming Zhang, Sirong Chen +9
In the context of newly release software frameworks, large language models (LLMs) often exhibit poor performance and a high rate of hallucination, as they are not exposed to such e…
cs.AI2025
Data Dependency-Aware Code Generation from Enhanced UML Sequence Diagrams
Wenxin Mao, Zhitao Wang, Long Wang +7
Large language models (LLMs) excel at generating code from natural language (NL) descriptions. However, the plain textual descriptions are inherently ambiguous and often fail to ca…