Free standard shipping on all orders
  • Visa
  • Master Card
  • American Express
  • Apple Pay
  • Google Pay
  • JCB

When NLP meets LLM: Neural Approaches to Context-based Conversational Question Answering book cover

1st Edition

When NLP meets LLM Neural Approaches to Context-based Conversational Question Answering

By Munazza Zaib, Quan Z. Sheng, Wei Emma Zhang, Adnan Mahmood Copyright 2026
102 Pages 21 B/W Illustrations
by CRC Press

102 Pages 21 B/W Illustrations
by CRC Press
Also available as eBook on:
This book looks at conversational search in intelligent dialogue systems, as it investigates and addresses the challenges pertinent to effective context incorporation in conversational question answering (ConvQA). The authors explore the possibility of designing a scalable Conversational Question Answering Agent that can handle the challenges of incomplete/ambiguous questions, better able to... Read more

1. Introduction 2. Role of Conversational Question Answering in Artificial Intelligence 3. Resolving Conversational Dependencies in Conversational Question Answering 4. Dynamic History Selection for Conversational Question Answering 5. History Modeling for Open-Domain Conversational Question Answering 6. Conclusion and Future Directions

Biography

Munazza Zaib is currently a Postdoctoral Research Fellow at the Department of Human Centred Computing, Faculty of Information Technology, Monash University, Australia.

Quan Z. Sheng is a Distinguished Professor and Head of School of Computing at Macquarie University, Australia. ). He is the recipient of the AMiner Most Influential Scholar Award on IoT (2007-2017), ARC (Australian Research Council) Future Fellowship (2014).

Wei Emma Zhang is Associate Head of People and Culture at the School of Computer and Mathematical Sciences, and a researcher at the Australian Institute for Machine Learning, the University of Adelaide.

Adnan Mahmood is a Lecturer in Computing – IoT and Networking at the School of Computing, Macquarie University, Sydney.

Add to Cart