When NLP meets LLM
Neural Approaches to Context-based Conversational Question Answering
Taylor & Francis Ltd
ISBN 978-1-03-297084-4
Standardpreis
Bibliografische Daten
Buch. Hardcover
2025
21 s/w-Abbildungen, 21 s/w-Zeichnungen, 13 s/w-Tabelle.
In englischer Sprache
Umfang: 102 S.
Format (B x L): 13.8 x 21.6 cm
Gewicht: 453
Verlag: Taylor & Francis Ltd
ISBN: 978-1-03-297084-4
Produktbeschreibung
This book aims to demonstrate that the history selection and modelling 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 conversational datasets and provide new insights into conversational information retrieval. Through a systematic study of structured representations, entity-aware history selection, and open-domain passage retrieval using contrastive learning, this book presents a robust framework for advancing multi-turn QA systems.
It is an essential resource for researchers, practitioners, and graduate students working at the intersection of NLP, dialogue systems, and intelligent information access.
Autorinnen und Autoren
Produktsicherheit
Hersteller
Libri GmbH
Europaallee 1
36244 Bad Hersfeld, DE
gpsr@libri.de