CAIR-Nepal researchers have contributed two chapters to Knowledge Graphs and Large Language Models: Current Approaches, Challenges, and Future Directions. The book is published by Academic Press, an imprint of Elsevier, in its Intelligent Data-Centric Systems series. Both chapters were led by CAIR-Nepal research interns, and the authors' copies arrived during Dashain, making this a festival gift for the team.
The book is edited by Sanju Tiwari (Sharda University, India), Sven Groppe and Jinghua Groppe (TU Bergakademie Freiberg, Germany), and Nandana Mihindukulasooriya (IBM Research, United States). It brings together current research on how knowledge graphs and large language models can be combined, along with the open challenges and future directions in the field.
Chapter 3: Knowledge graphs: structure, function, and significance
Niraj Karki, Nabin Oli, and Tek Raj Chhetri
This chapter introduces knowledge graphs: how they are structured, how they work, and why they matter. It provides a foundation for the more specialised chapters in the book.
Chapter 9: Integrating knowledge graphs and large language models for bias mitigation
Abhash Shrestha and Tek Raj Chhetri
This chapter examines how knowledge graphs can be combined with large language models to help reduce bias. The topic connects to CAIR-Nepal's wider work on trustworthy and responsible AI.