Multimodal Information Extraction
Multimodal Information Extraction is a computational process that identifies and structurally represents salient, interconnected data elements from multiple heterogeneous modalities—such as text, image, audio, and video—by integrating cross-modal signals to produce unified, semantically coherent information structures.
260
Publications
14K
Citations
1.1K
Authors
359
Institutions
Publications per year
2017–2026
179
Parents
260
Integrating Multimodal Information in Large Pretrained Transformers
Wasifur Rahman, Md. Kamrul Hasan, Sangwu Lee et al. · 2020 · 604 citations · Full text
Towards multimodal sentiment analysis
Louis‐Philippe Morency, Rada Mihalcea, Payal Doshi · 2011 · 455 citations
Annotating Multi-media/Multi-modal Resources with ELAN
Hennie Brugman, Albert Russel · 2004 · 407 citations · Full text
1–5 of 260
1.1K
Indraprastha Institute of Information Technology Delhi, India
6 publications · 237 citations
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3
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1–5 of 1.1K
359

Chinese Academy of Sciences
Beijing, China
15 h-index
53 publications
2.2K citations
University of Chinese Academy of Sciences
Beijing, China
12 h-index
40 publications
2.1K citations
National University of Singapore
Singapore, Singapore
12 h-index
32 publications
2.1K citations
Tsinghua University
Beijing, China
11 h-index
45 publications
1.8K citations
University of Science and Technology of China
Hefei, China
9 h-index
26 publications
662 citations

Sun Yat-sen University
Guangzhou, China
7 h-index
21 publications
932 citations
Carnegie Mellon University
Pittsburgh, United States
6 h-index
14 publications
835 citations
Institute of Computing Technology
Beijing, China
6 h-index
17 publications
1.1K citations
1–8 of 359
Repository · 11 publications · 388 citations
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Conference · 9 publications · 853 citations
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8 publications · 853 citations
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7 publications · 260 citations
6
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Conference · 5 publications · 194 citations
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