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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.IR2026
Revisiting Content-Based Music Recommendation: Efficient Feature Aggregation from Large-Scale Music Models
Yizhi Zhou, Jia-Qi Yang, De-Chuan Zhan +1
Music Recommendation Systems (MRSs) are a cornerstone of modern streaming platforms. Existing recommendation models, spanning both recall and ranking stages, predominantly rely on…