Summary

This talk discusses integrating Large Language Models (LLMs) into Pinterest's search relevance system. The presenters, machine learning engineers from Pinterest, detail their cross-encoder model architecture that leverages LLMs to predict the relevance of pins to user queries on a five-point scale. The primary takeaway is that LLMs are effective at improving search relevance through their ability to capture nuanced interactions between queries and content.