Question Answering
Question Answering is a natural language processing task that involves automatically determining precise answers to natural language questions by analyzing and understanding textual content, distinguished from related information retrieval or text mining tasks by its focus on identifying specific, factually grounded responses rather than retrieving, summarizing, or categorizing documents or passages.
11.2K
Publications
854.7K
Citations
26K
Authors
3.6K
Institutions
Publications per year
2017–2026
6.2K
11.2K
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das et al. · 2017 · 21.6K citations
Convolutional Neural Networks for Sentence Classification
1–5 of 11.2K
26K
36
h-index
35
h-index
33
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33
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32
h-index
1–5 of 26K
3.6K
Google (United States)
Mountain View, United States
77 h-index
782 publications
334.1K citations
University of Washington
Seattle, United States
73 h-index
489 publications
53.3K citations
Carnegie Mellon University
Pittsburgh, United States
71 h-index
605 publications
62.9K citations
Stanford University
Stanford, United States
69 h-index
451 publications
102.1K citations
Microsoft (United States)
Redmond, United States
66 h-index
507 publications
65.7K citations
Microsoft Research (United Kingdom)
Cambridge, United Kingdom
59 h-index
387 publications
51.8K citations

Chinese Academy of Sciences
Beijing, China
53 h-index
487 publications
29.2K citations
Microsoft Research Asia (China)
Beijing, China
51 h-index
284 publications
24.8K citations
1–8 of 3.6K
Repository · 1.3K publications · 108.3K citations
138
h-index
Conference · 254 publications · 17.3K citations
69
h-index
TACL · 54 publications · 7.5K citations
36
h-index
86 publications · 3.8K citations
34
h-index
56 publications · 1.9K citations
29
h-index
1–5