From Scoring to Spelling: Rebuilding Ads Retrieval at Instacart

This post details the transition from a BERT-based sequence model for ads retrieval that scored products to a generative model that spells out product recommendations token by token. The core technical innovation is the introduction of Instacart Semantic IDs (SIDs), generated by an RQ-VAE, which compress the product vocabulary by 125x and allow for better generalization and coverage of new products. The training data construction was also updated to use a 'Context Template' which enriches historical shopping sessions with new context tokens, moving from memorizing co-occurrences to generalizing based on semantic concepts. This enables better contextual matching and discovery of products, including those with zero transaction history.