7 papers
Compartment-driven Gaussian processes for uncertainty quantification of pharmacokinetic exposures
Sanjay Palta-Hill, Barbara Engelhardt, Edric Tam
Pharmacokinetic modeling is a crucial part of drug development. An important goal is to estimate patients' total and peak exposure to a drug over time, quantified by the area under…
CodeChat-Eval: Evaluating Large Language Models in Multi-Turn Code Refinement Dialogues
Guoxiang Guo, Kla Tantithamthavorn, Neelofar Neelofar +2
Large Language Models (LLMs) are increasingly used in software engineering to generate and refine code. In practice, developers often continue from an initial code generation reque…
UntrustVul: An Automated Approach for Identifying Untrustworthy Alerts in Vulnerability Detection Models
Lam Nguyen Tung, Xiaoning Du, Neelofar Neelofar +1
Machine learning (ML) has shown promise in vulnerability detection, but ML detectors may rely on irrelevant code features, causing them to highlight non-vulnerable lines as suspici…
MORTAR: Multi-turn Metamorphic Testing for LLM-based Dialogue Systems
Aaron Guoxiang Guo, Aldeida Aleti, Neelofar Neelofar +3
With the widespread application of LLM-based dialogue systems in daily life, quality assurance has become more important than ever. Recent research has successfully introduced meth…
Automated Trustworthiness Oracle Generation for Machine Learning Text Classifiers
Lam Nguyen Tung, Steven Cho, Xiaoning Du +4
Machine learning (ML) for text classification has been widely used in various domains. These applications can significantly impact ethics, economics, and human behavior, raising se…
Towards Reliable AI: Adequacy Metrics for Ensuring the Quality of System-level Testing of Autonomous Vehicles
Neelofar Neelofar, Aldeida Aleti
AI-powered systems have gained widespread popularity in various domains, including Autonomous Vehicles (AVs). However, ensuring their reliability and safety is challenging due to t…
Identifying and Explaining Safety-critical Scenarios for Autonomous Vehicles via Key Features
Neelofar, Aldeida Aleti
Ensuring the safety of autonomous vehicles (AVs) is of utmost importance and testing them in simulated environments is a safer option than conducting in-field operational tests. Ho…