8 papers
SWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Multi-Faceted Bug Reproduction Tests
Yaoqi Guo, Yang Liu, Jie M. Zhang +3
Large language model (LLM)-based software engineering agents are increasingly developed to resolve software issues by generating patches from issue reports and code repositories. B…
Fairness Testing of Large Language Models in Role-Playing
Xinyue Li, Zhenpeng Chen, Jie M. Zhang +6
Large Language Models (LLMs) have become foundational in modern language-driven software applications, profoundly influencing daily life. A critical technique in leveraging their p…
EET: Experience-Driven Early Termination for Cost-Efficient Software Engineering Agents
Yaoqi Guo, Ying Xiao, Jie M. Zhang +4
Software engineering (SE) agents powered by large language models are increasingly adopted in practice, yet they often incur substantial monetary cost. We introduce EET, an experie…
LLMs Are Not a Silver Bullet: A Case Study on Software Fairness
Xinyue Li, Sixuan Li, Ying Xiao +4
Fairness is a critical requirement for human-related, high-stakes software systems, motivating extensive research on bias mitigation. Prior work has largely focused on tabular data…
FairMedQA: Benchmarking Bias in Large Language Models for Medical Question Answering
Ying Xiao, Jie Huang, Ruijuan He +6
Large language models (LLMs) are approaching expert-level performance in medical question answering (QA), demonstrating strong potential to improve public healthcare. However, unde…
Software Fairness Dilemma: Is Bias Mitigation a Zero-Sum Game?
Zhenpeng Chen, Xinyue Li, Jie M. Zhang +5
Fairness is a critical requirement for Machine Learning (ML) software, driving the development of numerous bias mitigation methods. Previous research has identified a leveling-down…