2 citations · 3 across the 6 of their papers we have counts for
7 papers
ClinicBot: A Guideline-Grounded Clinical Chatbot with Prioritized Evidence RAG and Verifiable Citations
Navapat Nananukul, Mayank Kejriwal
Clinical diagnosis requires answers that are accurate, verifiable, and explicitly grounded in official guidelines. While large language models excel at natural language processing,…
An Analysis of Artificial Intelligence Adoption in NIH-Funded Research
Navapat Nananukul, Mayank Kejriwal
Understanding the landscape of artificial intelligence (AI) and machine learning (ML) adoption across the National Institutes of Health (NIH) portfolio is critical for research fun…
LOGicalThought: Logic-Based Ontological Grounding of LLMs for High-Assurance Reasoning
Navapat Nananukul, Yue Zhang, Ryan Lee +5
High-assurance reasoning, particularly in critical domains such as law and medicine, requires conclusions that are accurate, verifiable, and explicitly grounded in evidence. This r…
What if Red Can Talk? Dynamic Dialogue Generation Using Large Language Models
Navapat Nananukul, Wichayaporn Wongkamjan
Role-playing games (RPGs) provide players with a rich, interactive world to explore. Dialogue serves as the primary means of communication between developers and players, manifesti…
Unsupervised Federated Domain Adaptation for Segmentation of MRI Images
Navapat Nananukul, Hamid Soltanian-zadeh, Mohammad Rostami
Automatic semantic segmentation of magnetic resonance imaging (MRI) images using deep neural networks greatly assists in evaluating and planning treatments for various clinical app…
HALO: An Ontology for Representing and Categorizing Hallucinations in Large Language Models
Navapat Nananukul, Mayank Kejriwal
Recent progress in generative AI, including large language models (LLMs) like ChatGPT, has opened up significant opportunities in fields ranging from natural language processing to…
Cost-Efficient Prompt Engineering for Unsupervised Entity Resolution
Navapat Nananukul, Khanin Sisaengsuwanchai, Mayank Kejriwal
Entity Resolution (ER) is the problem of semi-automatically determining when two entities refer to the same underlying entity, with applications ranging from healthcare to e-commer…