3 papers
cs.IR2025
LongRetriever: Towards Ultra-Long Sequence based Candidate Retrieval for Recommendation
Qin Ren, Zheng Chai, Xijun Xiao +2
Precisely modeling user ultra-long sequences is critical for industrial recommender systems. Current approaches predominantly focus on leveraging ultra-long sequences in the rankin…
cs.IR2025
LONGER: Scaling Up Long Sequence Modeling in Industrial Recommenders
Zheng Chai, Qin Ren, Xijun Xiao +14
Modeling ultra-long user behavior sequences is critical for capturing both long- and short-term preferences in industrial recommender systems. Existing solutions typically rely on…
cs.IR2025
Adaptive Domain Scaling for Personalized Sequential Modeling in Recommenders
Zheng Chai, Hui Lu, Di Chen +3
Users generally exhibit complex behavioral patterns and diverse intentions in multiple business scenarios of super applications like Douyin, presenting great challenges to current…