Farid
Reliable Large Models with Knowledge Augmentation
by Wenguang Wang
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
ISBN: • Publisher: Springer Nature Singapore • Year: 2026
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
🌐 [color=#55acee]Language: English
📄 [color=#44bb44]Pages: 457
📋 [color=#ff9900]INFO: English | July 10, 2026 | ISBN-10: 9819573459 | 468 pages| Epub PDF (True) | 113 MB
📝 [color=#888888]DESCRIPTION: In the rapidly evolving landscape of artificial intelligence, large language models (LLMs) have emerged as transformative tools, yet they face persistent challenges such as hallucination, knowledge obsolescence, and limited reasoning depth. The book "Knowledge-Enhanced Large Models" addresses these gaps head-on, offering a comprehensive roadmap for integrating structured knowledge systems―particularly knowledge graphs―with cutting-edge AI models to build more reliable, accurate, and context-aware intelligent systems. This book is tailored for AI researchers, data scientists, engineers, students, and practitioners seeking to harness the synergy between large models and knowledge representation technologies. It balances theoretical rigor with practical implementation, making it equally valuable for academic exploration and industrial application.
📦 [color=#ff9900]Download Info
Folder: Reliable Large Models With Knowledge Augmentation
Format: EPUB
Total Size: 114.41 MB
📋 File List:
[size=2]
📌 978.981.95.7346.2.epub (Wenguang Wang) (2026) (72.75 MB)
📌 978.981.95.7346.2.pdf (Wenguang Wang) (41.66 MB)
————————————*****————————————
🔗RapidGator
https://rapidgator.net/file/97cc415c25c69e7c823c370a4140d717/Reliable.Large.Models.With.Knowledge.Augmentation.rar
🔗NitroFlare
https://nitroflare.com/view/5CE5FA61835597F/Reliable.Large.Models.With.Knowledge.Augmentation.rar?referrer=1635666
