AI RESEARCH
End-to-End Semantic ID Generation for Generative Advertisement Recommendation
arXiv CS.LG
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ArXi:2602.10445v3 Announce Type: replace-cross Generative Recommendation (GR) has excelled by framing recommendation as next-token prediction. This paradigm relies on Semantic IDs (SIDs) to tokenize large-scale items into discrete sequences. Existing GR approaches predominantly generate SIDs via Residual Quantization (RQ), where items are encoded into embeddings and then quantized to discrete SIDs.