4 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.IR2026
Teacher Retains Full Tokens, Student Merges Efficiently: TM20K for E-Commerce Sequence Modeling in Ad Recommendation
Xinchun Li, Duoru Zheng, Wenlin Zhao +13
Benefiting from ultra-long behavior sequence modeling, existing recommender systems bring users a better experience via simultaneously considering their long-term and short-term in…
cs.IR2026
MMRM: A Multiplex Multimodal Representation Model for Product Ranking in E-commerce Search
Zhen-Lin Chen, Maosen Sheng, Peng Lin +4
Multimodal information is pivotal for e-commerce search ranking. Existing works leverage multimodal data typically by fine-tuning general Multimodal Large Language Models (MLLMs) v…
cs.IR2024★ 4 cited
PPM : A Pre-trained Plug-in Model for Click-through Rate Prediction
Yuanbo Gao, Peng Lin, Dongyue Wang +4
Click-through rate (CTR) prediction is a core task in recommender systems. Existing methods (IDRec for short) rely on unique identities to represent distinct users and items that h…