Interactive Natural Language Processing

Language Model as Agent
Erscheinungsjahr 2026
ISBN: 978-3-032-06263-5
Verlag: Springer-Verlag GmbH

Buch, Englisch, 227 Seiten, Format (B × H): 168 mm x 240 mm

Reihe: Synthesis Lectures on Human Language Technologies

This book addresses the emergence of Interactive Natural Language Processing (iNLP) and its novel paradigm within the field of NLP and discusses the limitations in existing frameworks while aligning with the ultimate goals of artificial intelligence. This paradigm considers language models as agents capable of observing, acting, and receiving feedback iteratively from external entities.  The book provides a comprehensive survey of iNLP, starting by proposing a unified definition and framework of the concept. In addition, it provides a systematic classification of iNLP and dissects its various components, including interactive objects, interaction interfaces, and interaction methods.  The book then proceeds to delve into the evaluation methodologies used in the field and explores its diverse applications, scrutinizes its ethical and safety issues, and discusses prospective research directions. This work aims to be an entry point for researchers who are interested in this rapidly evolving area and offers a broad view of the current landscape and future trajectory of iNLP.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Wang, Zekun

Zhang, Ge

Lin, Chenghua

Fu, Jie

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion
• Mathematik | Informatik EDV | Informatik Angewandte Informatik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

Introduction.- Interactive Objects.- Interaction Interface.- Interaction Methods.- Evaluation.- Application.- Ethics and Safety.- Future Directions.- Conclusion.

Über Autor(innen)

Zekun Wang is a graduate student at Beihang University. Previously, he interned at Beijing Academy of Artificial Intelligence and ByteDance. He is currently at KlingAI from Kuaishou Technology. His research focuses on Large Language Models and Multimodal Large Language Models.

Ge Zhang is currently pursing a Ph.D. degree at the University of Waterloo. His research interests include music generation, self-supervised learning, and natural language processing, specifically human moral value alignment.

Chenghua Lin is a Full Professor and Chair in Natural Language Processing in the Department of Computer Science at the University of Manchester. His research focuses on the integration of machine learning and natural language processing for language generation and understanding. He also serves as Chair of the ACL SIGGEN Board and is a member of the IEEE Speech and Language Processing Technical Committee.

Jie Fu, Ph.D., is a visiting scholar at Hong Kong University of Science and Technology. He obtained his Ph.D. from the National University of Singapore and did his postdoctoral training at Quebec AI Institute (Mila). His reearch focuses on deep learning and large languge models.