Explainable Visual Question Answering
Explainable Visual Question Answering is a visual question answering paradigm that, as an extension of standard visual question answering, incorporates mechanisms to generate human-interpretable justifications or rationales for its answers, thereby exposing the reasoning process and grounding of multimodal inferences.
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3.5K
Citations
172
Authors
66
Institutions
Publications per year
2017–2026
54
Variants
Explainable Vqa
Parents
57
Counterfactual Samples Synthesizing for Robust Visual Question Answering
Grad-CAM: Why did you say that?
Ramprasaath R. Selvaraju, Abhishek Das, Ramakrishna Vedantam et al. · arXiv (Cornell University) · 2016 · 327 citations · Full text
Explicit Knowledge-based Reasoning for Visual Question Answering
Peng Wang, Qi Wu, Chunhua Shen et al. · 2017 · 173 citations · Full text
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The University of Texas at Austin
Austin, United States
4 h-index
9 publications
473 citations
Nanyang Technological University
Singapore, Singapore
4 h-index
6 publications
462 citations

Chinese Academy of Sciences
Beijing, China
3 h-index
5 publications
505 citations
University of Science and Technology of China
Hefei, China
3 h-index
4 publications
169 citations

University of Rochester
Rochester, United States
3 h-index
6 publications
226 citations
University of Chinese Academy of Sciences
Beijing, China
3 h-index
6 publications
608 citations

Zhejiang University
Hangzhou, China
3 h-index
10 publications
1.6K citations
Meta (Israel)
Tel Aviv, Israel
3 h-index
6 publications
252 citations
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Repository · 19 publications · 1.2K citations
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Conference · 2 publications · 130 citations
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2 publications · 30 citations
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2 publications · 123 citations
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2 publications · 235 citations
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