Unified Multimodal Model with Unlikelihood Training for Visual Dialog

Author:

Wang Zihao1,Wang Junli1,Jiang Changjun1

Affiliation:

1. Tongji University, Shanghai, China

Funder

The National Key Research and Development Program of China

Publisher

ACM

Reference43 articles.

1. History for Visual Dialog: Do we really need it?

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3. VQA: Visual Question Answering

4. Multimodal Machine Learning: A Survey and Taxonomy

5. Hangbo Bao , Li Dong , Furu Wei , Wenhui Wang , Nan Yang , Xiaodong Liu , Yu Wang , Jianfeng Gao , Songhao Piao , Ming Zhou , and Hsiao-Wuen Hon . 2020 . UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training . In Proceedings of the 37th International Conference on Machine Learning (Proceedings of Machine Learning Research , Vol. 119), , Hal Daumé III and Aarti Singh (Eds.). PMLR, 642--652. https://proceedings.mlr.press/v119/bao20a.html Hangbo Bao, Li Dong, Furu Wei, Wenhui Wang, Nan Yang, Xiaodong Liu, Yu Wang, Jianfeng Gao, Songhao Piao, Ming Zhou, and Hsiao-Wuen Hon. 2020. UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training. In Proceedings of the 37th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 119), , Hal Daumé III and Aarti Singh (Eds.). PMLR, 642--652. https://proceedings.mlr.press/v119/bao20a.html

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