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Generative Retrieval for E-commerce: Jointly Learning Embedding and Codebook with Same Product Cluster

arXiv · AI, language, vision and robotics · article · Aug 31, 2026 · UTC

With the development of large language models (LLMs), generative retrieval is becoming increasingly important in e-commerce scenarios. Current mainstream approaches typically use a two-stage training strategy: first train a product embedding model, and then learn a codebook that maps embeddings to product IDs. This cascaded approach suffers from two major issues: (1) error accumulation-if the embedding model in the first stage produces biased representations, the codebook in the second stage cannot correct these errors, degrading final retrieval performance; and (2) codebook learning relies so

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