Session Outline
LLMs have emerged as powerful tools for a wide range of NLP tasks. Recently, there has been a significant amount of interest in recommender system community in using LLMs to enhance various aspects of recommender systems. This talk explains how LLMs are being incorporated in recommender systems, why should LLMs be used for building recommenders, and what are some of the associated challenges.
Key Takeaways
- Ways to utilize Generative LLMs for building recommender systems, including zero-shot, few-shot and fine-tuning methods.
- A review of the very recent research on this theme from academic and industrial labs.
- Understand the associated pros, cons, open questions and challenges of using LLMs for recommendations.
