87 citations · 166 across the 14 of their papers we have counts for
4 papers · 1 filter
From Consensus to Disagreement: Multi-Teacher Distillation for Semi-Supervised Relation Extraction
Wanli Li, Tieyun Qian
Lack of labeled data is a main obstacle in relation extraction. Semi-supervised relation extraction (SSRE) has been proven to be a promising way for this problem through annotating…
Multi-Scale Feature and Metric Learning for Relation Extraction
Mi Zhang, Tieyun Qian
Existing methods in relation extraction have leveraged the lexical features in the word sequence and the syntactic features in the parse tree. Though effective, the lexical feature…
Intent Disentanglement and Feature Self-supervision for Novel Recommendation
Tieyun Qian, Yile Liang, Qing Li +3
One key property in recommender systems is the long-tail distribution in user-item interactions where most items only have few user feedback. Improving the recommendation of tail i…
Recommending Accurate and Diverse Items Using Bilateral Branch Network
Yile Liang, Tieyun Qian
Recommender systems have played a vital role in online platforms due to the ability of incorporating users' personal tastes. Beyond accuracy, diversity has been recognized as a key…