30 citations · 233 across the 58 of their papers we have counts for
9 papers · 1 filter
Understanding and Estimating Domain Complexity Across Domains
Katarina Doctor, Mayank Kejriwal, Lawrence Holder +5
Artificial Intelligence (AI) systems, trained in controlled environments, often struggle in real-world complexities. We propose a general framework for estimating domain complexity…
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…
A Knowledge Graph-Based Search Engine for Robustly Finding Doctors and Locations in the Healthcare Domain
Mayank Kejriwal, Hamid Haidarian, Min-Hsueh Chiu +3
Efficiently finding doctors and locations is an important search problem for patients in the healthcare domain, for which traditional information retrieval methods tend not to work…
A Formalism and Approach for Improving Robustness of Large Language Models Using Risk-Adjusted Confidence Scores
Ke Shen, Mayank Kejriwal
Large Language Models (LLMs), such as ChatGPT, have achieved impressive milestones in natural language processing (NLP). Despite their impressive performance, the models are known…
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…
Named Entity Resolution in Personal Knowledge Graphs
Mayank Kejriwal
Entity Resolution (ER) is the problem of determining when two entities refer to the same underlying entity. The problem has been studied for over 50 years, and most recently, has t…