Can I read When Nlp Meets LLM Neural Approaches to Context-Based Conversational Question Answering on EtoBox?

When Nlp Meets LLM Neural Approaches to Context-Based Conversational Question Answering by Munazza Zaib, Quan Z. Sheng, Wei Emma Zhang, Adnan Mahmood is a book available to read on EtoBox.

What is When Nlp Meets LLM Neural Approaches to Context-Based Conversational Question Answering about?

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 relate to co-references to cope with the problems of effective weights and optimal threshold selection in vehicular networks. A fundamental emphasis is the understanding of ambiguous follow-up questions and the generation of contextual and question entities to fill in the missing information gaps. Key topics are studied, such as “hard history selection” to filter out the context that is not relevant and performing a re-ranking of the selected turns based on their significance to answer the question as a part of the soft history selection process. This book aims to demonstrate that the history selection and modeling approaches proposed can effectively improve the performance of ConvQA models in different settings. The proposed models are compared with the state-of-the-art vis-à-vis different con

Author

Munazza Zaib, Quan Z. Sheng, Wei Emma Zhang, Adnan Mahmood

Publisher

CRC Press LLC

Published

2025

Language

EN

ISBN

9781032970844