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cs.IR2026

Generative Recommenders Forget the Long Tail: Restoring Memorization in Retrieval and Ranking

Xu Huang, Jiancan Wu, Hongzheng Qin +5

Generative recommenders replace the retrieve-then-rank cascade with a single model: beam search over semantic item identifiers performs retrieval, and the same likelihood performs…

cs.IR2025

LLM-Aligned Geographic Item Tokenization for Local-Life Recommendation

Hao Jiang, Guoquan Wang, Donglin Zhou +5

Recent advances in Large Language Models (LLMs) have enhanced text-based recommendation by enriching traditional ID-based methods with semantic generalization capabilities. Text-ba…

cs.IR2025

ReST: A Plug-and-Play Spatially-Constrained Representation Enhancement Framework for Local-Life Recommendation

Hao Jiang, Long Zhang, Guoquan Wang +6

Local-life recommendation have witnessed rapid growth, providing users with convenient access to daily essentials. However, this domain faces two key challenges: (1) spatial constr…

cs.IR2025

OneLoc: Geo-Aware Generative Recommender Systems for Local Life Service

Zhipeng Wei, Kuo Cai, Junda She +8

Local life service is a vital scenario in Kuaishou App, where video recommendation is intrinsically linked with store's location information. Thus, recommendation in our scenario i…

cs.IR2025

FIM: Frequency-Aware Multi-View Interest Modeling for Local-Life Service Recommendation

Guoquan Wang, Qiang Luo, Weisong Hu +4

People's daily lives involve numerous periodic behaviors, such as eating and traveling. Local-life platforms cater to these recurring needs by providing essential services tied to…