4 papers
Towards Exception Safety Code Generation with Intermediate Representation Agents Framework
Xuanming Zhang, Yuxuan Chen, Yuan Yuan +1
Large Language Models (LLMs) often struggle with robust exception handling in generated code, leading to fragile programs that are prone to runtime errors. We propose Seeker, a nov…
How Well Do Large Language Models Serve as End-to-End Secure Code Agents for Python?
Jianian Gong, Nachuan Duan, Ziheng Tao +3
The rapid advancement of large language models (LLMs) such as GPT-4 has revolutionized the landscape of software engineering, positioning these models at the core of modern develop…
SocialEval: Evaluating Social Intelligence of Large Language Models
Jinfeng Zhou, Yuxuan Chen, Yihan Shi +13
LLMs exhibit promising Social Intelligence (SI) in modeling human behavior, raising the need to evaluate LLMs' SI and their discrepancy with humans. SI equips humans with interpers…
Seeker: Towards Exception Safety Code Generation with Intermediate Language Agents Framework
Xuanming Zhang, Yuxuan Chen, Yiming Zheng +3
In real world software development, improper or missing exception handling can severely impact the robustness and reliability of code. Exception handling mechanisms require develop…