45 citations · 72 across the 8 of their papers we have counts for
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cs.IR2023★ 1 cited
Hierarchical Reinforcement Learning for Modeling User Novelty-Seeking Intent in Recommender Systems
Pan Li, Yuyan Wang, Ed H. Chi +1
Recommending novel content, which expands user horizons by introducing them to new interests, has been shown to improve users' long-term experience on recommendation platforms \cit…
cs.IR2023★ 4 cited
Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations
Pan Li, Yuyan Wang, Ed H. Chi +1
Existing aspect extraction methods mostly rely on explicit or ground truth aspect information, or using data mining or machine learning approaches to extract aspects from implicit…
cs.LG2023
URM4DMU: an user represention model for darknet markets users
Hongmeng Liu, Jiapeng Zhao, Yixuan Huo +5
Darknet markets provide a large platform for trading illicit goods and services due to their anonymity. Learning an invariant representation of each user based on their posts on di…