May 25, 2026 · Artificial Intelligence

How Adaptive Semantic IDs Enable Precise and Generalizable Generative Retrieval

The article introduces the SA²CRQ framework, which adaptively allocates semantic ID length and transfers residual knowledge to resolve head‑item ID collisions and tail‑item generalization gaps in large‑scale e‑commerce generative retrieval, achieving stable gains on both industrial and public datasets.

Adaptive QuantizationE-commerce SearchEmbedding

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How Adaptive Semantic IDs Enable Precise and Generalizable Generative Retrieval

JD Cloud Developers

May 28, 2025 · Artificial Intelligence

Uncovering the ‘Sandwich’ Bottleneck in Residual Quantized Semantic IDs for Generative Search

This study investigates the “sandwich” bottleneck observed in residual‑quantized semantic identifiers (RQ‑SID) used in generative search and recommendation systems, revealing that token concentration in intermediate codebooks caused by path sparsity and long‑tail distributions degrades performance, and proposes two effective mitigation strategies that improve efficiency and generalization in e‑commerce applications.

Long-tail Distributione-commerce recommendationgenerative search

0 likes · 13 min read