3 code implementations • ACL 2022 • Xuwu Wang, Junfeng Tian, Min Gui, Zhixu Li, Rui Wang, Ming Yan, Lihan Chen, Yanghua Xiao
In this paper, we present WikiDiverse, a high-quality human-annotated MEL dataset with diversified contextual topics and entity types from Wikinews, which uses Wikipedia as the corresponding knowledge base.
1 code implementation • NAACL 2022 • Xinyu Wang, Min Gui, Yong Jiang, Zixia Jia, Nguyen Bach, Tao Wang, Zhongqiang Huang, Fei Huang, Kewei Tu
As text representations take the most important role in MNER, in this paper, we propose {\bf I}mage-{\bf t}ext {\bf A}lignments (ITA) to align image features into the textual space, so that the attention mechanism in transformer-based pretrained textual embeddings can be better utilized.
Ranked #1 on Multi-modal Named Entity Recognition on Twitter-17
Multi-modal Named Entity Recognition named-entity-recognition +1
no code implementations • 21 Aug 2021 • Ming Yan, Haiyang Xu, Chenliang Li, Bin Bi, Junfeng Tian, Min Gui, Wei Wang
Existing approaches to vision-language pre-training (VLP) heavily rely on an object detector based on bounding boxes (regions), where salient objects are first detected from images and then a Transformer-based model is used for cross-modal fusion.
no code implementations • SEMEVAL 2021 • Junfeng Tian, Min Gui, Chenliang Li, Ming Yan, Wenming Xiao
We describe our systems of subtask1 and subtask3 for SemEval-2021 Task 6 on Detection of Persuasion Techniques in Texts and Images.
no code implementations • IJCNLP 2019 • Min Gui, Junfeng Tian, Rui Wang, Zhenglu Yang
Attention plays a key role in the improvement of sequence-to-sequence-based document summarization models.