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cs.IR2026
SequenceO1: End-to-End Ultra-Long (100K) Sequence Modeling in Recommendation with Low-Rank Caching
Lin Guan, Jia-Qi Yang, Zhishan Zhao +15
Modeling long-term user behavior is central to sequential recommendation and billion-scale industrial recommender systems, yet production ranking models operate under strict latenc…
cs.IR2025
RecGPT Technical Report
Chao Yi, Dian Chen, Gaoyang Guo +51
Recommender systems are among the most impactful applications of artificial intelligence, serving as critical infrastructure connecting users, merchants, and platforms. However, mo…
cs.IR2024
Simple but Efficient: A Multi-Scenario Nearline Retrieval Framework for Recommendation on Taobao
Yingcai Ma, Ziyang Wang, Yuliang Yan +5
In recommendation systems, the matching stage is becoming increasingly critical, serving as the upper limit for the entire recommendation process. Recently, some studies have start…