Jianqiang (Jay) Wang is an AI and data science leader with over 16 years of experience developing machine learning, search, and recommendation systems across leading tech companies including Microsoft, Snap, Twitter, and Kuaishou. He has led data science and AI teams and built large-scale systems for content understanding, personalization, and monetization.
Jay is the founder of Curify AI, an AI-powered productivity and content platform, where he focuses on integrating Large Language Models into real-world applications. His current interests span retrieval-augmented generation, multimodal AI, and generative recommendation systems.
He holds a Ph.D. in Statistics and brings a blend of academic rigor and industrial experience to this hands-on guide for building LLM-enhanced recommendation systems.
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Building Recommender Systems Using Large Language Models
Jianqiang (Jay) Wang
Chapter 1 Introduction to LLMs.- Chapter 2 From Traditional to LLM-powered Recommendation Systems.- Chapter 3 LLM-enhanced recommendation system.- Chapter 4 LLM as recommendation system.- Chapter 5 Conversational recommendation systems.- Chapter 6 Leveraging Multi-Modal Data.- Chapter 7 Generative Recommendation and Planning Systems.- Chapter 8 Challenges and Trends in LLMs for Recommendation Systems.
