4 papers
Efficient Fairness Testing in Large Language Models: Prioritizing Metamorphic Relations for Bias Detection
Suavis Giramata, Madhusudan Srinivasan, Venkat Naidu Gudivada +1
Large Language Models (LLMs) are increasingly deployed in various applications, raising critical concerns about fairness and potential biases in their outputs. This paper explores…
Metamorphic Testing for Fairness Evaluation in Large Language Models: Identifying Intersectional Bias in LLaMA and GPT
Harishwar Reddy, Madhusudan Srinivasan, Upulee Kanewala
Large Language Models (LLMs) have made significant strides in Natural Language Processing but remain vulnerable to fairness-related issues, often reflecting biases inherent in thei…
Testing Research Software: An In-Depth Survey of Practices, Methods, and Tools
Nasir U. Eisty, Upulee Kanewala, Jeffrey C. Carver
Context: Research software is essential for developing advanced tools and models to solve complex research problems and drive innovation across domains. Therefore, it is essential…
Optimizing Metamorphic Testing: Prioritizing Relations Through Execution Profile Dissimilarity
Madhusudan Srinivasan, Upulee Kanewala
An oracle determines whether the output of a program for executed test cases is correct. For machine learning programs, such an oracle is often unavailable or impractical to apply.…