8 citations · 9 across the 5 of their papers we have counts for
5 papers
Context-based and Diversity-driven Specificity in Compositional Zero-Shot Learning
Yun Li, Zhe Liu, Hang Chen +1
Compositional Zero-Shot Learning (CZSL) aims to recognize unseen attribute-object pairs based on a limited set of observed examples. Current CZSL methodologies, despite their advan…
E-NER: Evidential Deep Learning for Trustworthy Named Entity Recognition
Zhen Zhang, Mengting Hu, Shiwan Zhao +6
Most named entity recognition (NER) systems focus on improving model performance, ignoring the need to quantify model uncertainty, which is critical to the reliability of NER syste…
Auto-weighted Multi-view Clustering for Large-scale Data
Xinhang Wan, Xinwang Liu, Jiyuan Liu +6
Multi-view clustering has gained broad attention owing to its capacity to exploit complementary information across multiple data views. Although existing methods demonstrate deligh…
Distilled Reverse Attention Network for Open-world Compositional Zero-Shot Learning
Yun Li, Zhe Liu, Saurav Jha +2
Open-World Compositional Zero-Shot Learning (OW-CZSL) aims to recognize new compositions of seen attributes and objects. In OW-CZSL, methods built on the conventional closed-world…
An Entropy-guided Reinforced Partial Convolutional Network for Zero-Shot Learning
Yun Li, Zhe Liu, Lina Yao +3
Zero-Shot Learning (ZSL) aims to transfer learned knowledge from observed classes to unseen classes via semantic correlations. A promising strategy is to learn a global-local repre…