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cs.IR2026
Restoring Collaborative Signals in Semantic-ID Generative Recommendation via Personalized Natural Language
Changjiang Han, Qingyang Li, Yaqiang Zang +4
Making LLM-based generative recommendation models stronger and more personalized through natural language and explicit reasoning is a widely anticipated yet still unsolved goal. Su…
cs.IR2026
Beyong Tokens: Item-aware Attention for LLM-based Recommendation
Xiaokun Zhang, Bowei He, Jiamin Chen +2
Large Language Models (LLMs) have recently gained increasing attention in the field of recommendation. Existing LLM-based methods typically represent items as token sequences, and…