7 citations · 13 across the 5 of their papers we have counts for
5 papers
A Positive-Unlabeled Metric Learning Framework for Document-Level Relation Extraction with Incomplete Labeling
Ye Wang, Huazheng Pan, Tao Zhang +2
The goal of document-level relation extraction (RE) is to identify relations between entities that span multiple sentences. Recently, incomplete labeling in document-level RE has r…
A Personality-Guided Preference Aggregator for Ephemeral Group Recommendation
Guangze Ye, Wen Wu, Liye Shi +3
Ephemeral group recommendation (EGR) aims to suggest items for a group of users who come together for the first time. Existing work typically consider individual preferences as the…
Self-Attentive Sequential Recommendation with Cheap Causal Convolutions
Jiayi Chen, Wen Wu, Liye Shi +5
Sequential Recommendation is a prominent topic in current research, which uses user behavior sequence as an input to predict future behavior. By assessing the correlation strength…
A Unified Positive-Unlabeled Learning Framework for Document-Level Relation Extraction with Different Levels of Labeling
Ye Wang, Xinxin Liu, Wenxin Hu +1
Document-level relation extraction (RE) aims to identify relations between entities across multiple sentences. Most previous methods focused on document-level RE under full supervi…
DACSR: Decoupled-Aggregated End-to-End Calibrated Sequential Recommendation
Jiayi Chen, Wen Wu, Liye Shi +4
Sequential recommendations have made great strides in accurately predicting the future behavior of users. However, seeking accuracy alone may bring side effects such as unfair and…