Vinted implemented dense retrieval using embedding-based search to solve low-recall problems in their multilingual e-commerce platform. The solution uses a Two-Tower Model with CLIP embeddings, processing over 1 billion items through Vespa's HNSW index. Key challenges included managing latency with filtered ANN searches,
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