26 citations · 55 across the 25 of their papers we have counts for
9 papers · 1 filter
Bias in Large Language Models: Origin, Evaluation, and Mitigation
Yufei Guo, Muzhe Guo, Juntao Su +5
Large Language Models (LLMs) have revolutionized natural language processing, but their susceptibility to biases poses significant challenges. This comprehensive review examines th…
Synthesizing Efficient and Permissive Programmatic Runtime Shields for Neural Policies
Jieke Shi, Junda He, Zhou Yang +2
With the increasing use of neural policies in control systems, ensuring their safety and reliability has become a critical software engineering task. One prevalent approach to ensu…
Hotfixing Large Language Models for Code
Zhou Yang, David Lo
Large Language Models for Code (LLM4Code) have become an integral part of developers' workflows, assisting with tasks such as code completion and generation. However, these models…
Ecosystem of Large Language Models for Code
Zhou Yang, Jieke Shi, Premkumar Devanbu +1
The availability of vast amounts of publicly accessible data of source code and the advances in modern language models, coupled with increasing computational resources, have led to…
AI Coders Are Among Us: Rethinking Programming Language Grammar Towards Efficient Code Generation
Zhensu Sun, Xiaoning Du, Zhou Yang +2
Artificial Intelligence (AI) models have emerged as another important audience for programming languages alongside humans and machines, as we enter the era of large language models…
Efficient and Green Large Language Models for Software Engineering: Literature Review, Vision, and the Road Ahead
Jieke Shi, Zhou Yang, David Lo
Large Language Models (LLMs) have recently shown remarkable capabilities in various software engineering tasks, spurring the rapid growth of the Large Language Models for Software…
Robustness, Security, Privacy, Explainability, Efficiency, and Usability of Large Language Models for Code
Zhou Yang, Zhensu Sun, Terry Zhuo Yue +2
Large language models for code (LLM4Code), which demonstrate strong performance (e.g., high accuracy) in processing source code, have significantly transformed software engineering…
Industry Practitioners Perspectives on AI Model Quality: Perceptions, Challenges, and Solutions
Chenyu Wang, Zhou Yang, Yunbo Lyu +3
Artificial Intelligence (AI) is now used across nearly every industry, making AI model quality essential for building reliable and trustworthy systems. Historically, correctness ha…
Assessing AI Detectors in Identifying AI-Generated Code: Implications for Education
Wei Hung Pan, Ming Jie Chok, Jonathan Leong Shan Wong +6
Educators are increasingly concerned about the usage of Large Language Models (LLMs) such as ChatGPT in programming education, particularly regarding the potential exploitation of…