7 citations · 17 across the 7 of their papers we have counts for
4 papers · 1 filter
Bias Testing and Mitigation in LLM-based Code Generation
Dong Huang, Jie M. Zhang, Qingwen Bu +3
As the adoption of LLMs becomes more widespread in software coding ecosystems, a pressing issue has emerged: does the generated code contain social bias and unfairness, such as tho…
CodeCoT: Tackling Code Syntax Errors in CoT Reasoning for Code Generation
Dong Huang, Qingwen Bu, Yuhao Qing +1
Chain-of-thought (CoT) has emerged as a groundbreaking tool in NLP, notably for its efficacy in complex reasoning tasks, such as mathematical proofs. However, its application in co…
Towards Building More Robust Models with Frequency Bias
Qingwen Bu, Dong Huang, Heming Cui
The vulnerability of deep neural networks to adversarial samples has been a major impediment to their broad applications, despite their success in various fields. Recently, some wo…
Feature Map Testing for Deep Neural Networks
Dong Huang, Qingwen Bu, Yahao Qing +2
Due to the widespread application of deep neural networks~(DNNs) in safety-critical tasks, deep learning testing has drawn increasing attention. During the testing process, test ca…