40 citations · 59 across the 13 of their papers we have counts for
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cs.IR2026
ClawRec: A Claw-Native Recommender System
Chenghao Wu, Kesha Ou, Xiaolei Wang +8
Recommender systems have become integral to navigating the modern digital ecosystem. Yet most deployed systems remain confined within single-platform boundaries, observing localize…
cs.IR2026
Deep Research for Recommender Systems
Kesha Ou, Chenghao Wu, Xiaolei Wang +6
The technical foundations of recommender systems have progressed from collaborative filtering to complex neural models and, more recently, large language models. Despite these tech…
cs.IR2024
EXIT: An EXplicit Interest Transfer Framework for Cross-Domain Recommendation
Lei Huang, Weitao Li, Chenrui Zhang +3
Cross-domain recommendation has attracted substantial interest in industrial apps such as Meituan, which serves multiple business domains via knowledge transfer and meets the diver…