arXiv Machine Learning August 11, 2026 By Donald Loveland, Liam Collins, Bhuvesh Kumar, Danai Koutra, Neil Shah

Preserving Item Semantics for Free: Rethinking Token Initialization in LLM-Based Generative Recommendation

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arXiv:2608. 07816v1 Announce Type: cross Abstract: Recent advances in generative recommendation (GR) leverage large language models (LLMs) as recommender backbones, enabling LLMs to directly generate recommendations conditioned on item-interaction histories.

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VaLiDRec: Variable-Length LLM-Aligned Semantic IDs for Generative Recommendation

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On the Memorization Behavior of LLMs in Generative Recommendation: Observations, Implications, and Training Strategies

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