SMART: LLM-Augmented Hybrid Retrieval for Dynamic Product Ads
Dynamic Product Ads (DPA) require retrieving relevant items from multi-million product catalogs, balancing two competing objectives: retargeting (re-surfacing known interests) and prospecting (discovering new categories). While Large Language Models (LLMs) capture semantic intent better than traditional embedding models, deploying them at scale introduces prohibitive inference costs and lexical mismatch issues. Through controlled experiments on millions of users, we demonstrate a critical retrieval decomposition: rule-generated queries excel at retargeting on a lexical BM25 index, while LLM-generated queries excel at prospecting on a dense ANN index. Building on this, we propose SMART (Se...
| Authors | Congfei Zhang, Jingxiao Ma, Xiaodong Liu et al. |
|---|---|
| Primary category | cs.IR |
| Published | 25 July 2026 |
| Last updated at source | 25 July 2026 |
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