LLM-Based Assistive Recommendation

Apr 1, 2024·
吳健雄
吳健雄
· 1 min read
Date
Apr 1, 2024 12:00 AM

Large Language Models (LLMs) have demonstrated impressive capabilities for natural language understanding and generation. What if we power recommender systems with LLMs that can reason through user activities on the platform, and can help plan recommendations accordingly? Equipped with UXR insights that people use nuanced language to describe their long-term interest journeys, and they want more user agency in their recommender platforms, we pinpoint a combination of LLMs and personalization as a key ingredient for the next generation of assistive recommendation.

吳健雄
Authors
Professor of Artificial Intelligence
My research interests include distributed robotics, mobile computing and programmable matter.