1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
MODRL-TA:A Multi-Objective Deep Reinforcement Learning Framework for Traffic Allocation in E-Commerce Search
Peng Cheng, Huimu Wang, Jinyuan Zhao +8
Traffic allocation is a process of redistributing natural traffic to products by adjusting their positions in the post-search phase, aimed at effectively fostering merchant growth,…
Attention Weighted Mixture of Experts with Contrastive Learning for Personalized Ranking in E-commerce
Juan Gong, Zhenlin Chen, Chaoyi Ma +7
Ranking model plays an essential role in e-commerce search and recommendation. An effective ranking model should give a personalized ranking list for each user according to the use…
Adversarial Mixture Of Experts with Category Hierarchy Soft Constraint
Zhuojian Xiao, Yunjiang jiang, Guoyu Tang +4
Product search is the most common way for people to satisfy their shopping needs on e-commerce websites. Products are typically annotated with one of several broad categorical tags…