1 code implementation • EMNLP 2020 • Zujie Liang, Weitao Jiang, Haifeng Hu, Jiaying Zhu
In the task of Visual Question Answering (VQA), most state-of-the-art models tend to learn spurious correlations in the training set and achieve poor performance in out-of-distribution test data.
1 code implementation • EMNLP 2021 • Zujie Liang, Huang Hu, Can Xu, Jian Miao, Yingying He, Yining Chen, Xiubo Geng, Fan Liang, Daxin Jiang
Second, only the items mentioned in the training corpus have a chance to be recommended in the conversation.
1 code implementation • 29 May 2021 • Zujie Liang, Haifeng Hu, Jiaying Zhu
Most existing Visual Question Answering (VQA) systems tend to overly rely on language bias and hence fail to reason from the visual clue.
1 code implementation • ACL 2021 • Zujie Liang, Huang Hu, Can Xu, Chongyang Tao, Xiubo Geng, Yining Chen, Fan Liang, Daxin Jiang
The retriever aims to retrieve a correlated image to the dialog from an image index, while the visual concept detector extracts rich visual knowledge from the image.