Session Outline
In this session at the Data Innovation Summit 2024, we have Konstantina Christakopoulou, Senior Research Engineer at Google DeepMind! Large Language Models (LLMs) have demonstrated impressive capabilities for natural language understanding and generation. But 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.
Key Takeaways
- Introduce a novel LLM-based journey service that allows to uncover the personalized nuanced user interests, needs and goals of users, i.e., their interest journeys, through fine-tuning and prompt-tuning LLMs.
- Research findings from this work on LLMs for better user understanding, and will provide insights on LLM-based long-term planning to assist user journeys.
- Provide challenges and opportunities across our long quest of integrating LLMs into user facing products to transform the user experience.
