The DOI matches its Crossref record; 70 of the 70 references it cites were found in a registry or an index.
Quantum-inspired multimodal fusion for video sentiment analysis
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Cites
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017) · arXiv · doi:10.48550/arxiv.1706.03762 · Cited by 120,404
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) · doi:10.18653/v1/n19-1423 · Cited by 54,325
XLNet: Generalized Autoregressive Pretraining for Language Understanding
Yang, Z., Dai, Z., Yang, Y., Carbonell, J., Salakhutdinov, R., & Le, Q. V. (2019) · arXiv · doi:10.48550/arxiv.1906.08237 · Cited by 6,687
Lipton, Z. C. (2018) · Queue · doi:10.1145/3236386.3241340 · Cited by 5,427
Quantum Computation and Quantum Information: 10th Anniversary Edition
Nielsen, M. A., & Chuang, I. L. (2011) · Cited by 2,724
Multimodal Transformer for Unaligned Multimodal Language Sequences
Tsai, Y.-H. H., Bai, S., Liang, P. P., Kolter, J. Z., Morency, L.-P., & Salakhutdinov, R. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/p19-1656 · Cited by 2,259 · cited 10×
“Multimodal Transformer (MulT) [8] takes a different approach by directly computing the inter-modal representations via the encoder of Transformer [34], resulting in a simpler but better-performed network.”
BackgroundMethodInfluentialTensor Fusion Network for Multimodal Sentiment Analysis
Zadeh, A., Chen, M., Poria, S., Cambria, E., & Morency, L.-P. (2017) · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d17-1115 · Cited by 2,102
Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph
Bagher Zadeh, A., Liang, P. P., Poria, S., Cambria, E., & Morency, L.-P. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/p18-1208 · Cited by 1,433 · cited 6×
“We evaluate our model by comparing it against state-of-the-art (SOTA) baselines on two benchmarking multimodal sentiment analysis datasets, namely CMU-MOSI [25] and CMU-MOSEI [6].”
BackgroundMethodInfluential
Research works printed but not linked: 1
- J. Wang, D. Song, K. Leszek, Tensor Product of Correlated Textual and Visual Features: A Quantum Theory Inspired Image Retrieval Framework, in: AAAI Fall Symposium Series, URL https://www.aaai.org/ocs/index.php/FSS/FSS10/paper/view/2297.
Cited by
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Gandhi, A., Adhvaryu, K., Poria, S., Cambria, E., & Hussain, A. (2023) · Information Fusion · doi:10.1016/j.inffus.2022.09.025 · Cited by 783
Multimodal sentiment analysis based on fusion methods: A survey
Zhu, L., Zhu, Z., Zhang, C., Xu, Y., & Kong, X. (2023) · Information Fusion · doi:10.1016/j.inffus.2023.02.028 · Cited by 375
Hybrid Contrastive Learning of Tri-Modal Representation for Multimodal Sentiment Analysis
Mai, S., Zeng, Y., Zheng, S., & Hu, H. (2022) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2022.3172360 · Cited by 307
Mai, S., Zeng, Y., & Hu, H. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2022.3171679 · Cited by 182
Multimodal Video Sentiment Analysis Using Deep Learning Approaches, a Survey
Abdu, S. A., Yousef, A. H., & Salem, A. (2021) · Information Fusion · doi:10.1016/j.inffus.2021.06.003 · Cited by 154
Metadata
- Authors
- Li, Q., Gkoumas, D., Lioma, C., & Melucci, M.
- Affiliations
- University of Padua (IT)
- The Open University (GB)
- University of Copenhagen (DK)
- Corresponding author
- Li, Qiuchi
- Venue
- Information Fusion
- Publisher
- Elsevier BV
- Published
- 2021-01
- Volume
- 65
- Pages
- 58-71
- ISSN
- 1566-2535 (ISSN-L)
- OpenAlex
- W3048195943
- Cited by
- 143
- References
- 65
- Citations by year
- 2026: 12 · 2025: 31 · 2024: 23 · 2023: 31 · 2022: 32 · 2021: 13
- FWCI
- 7.57
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Information Fusion (publishedVersion)
- Open Research Online (The Open University) (acceptedVersion)
- arXiv (Cornell University) (submittedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Padua Research Archive (University of Padova) (submittedVersion, cc-by-nc-nd)
- arXiv (Cornell University) (cc-by)
- Funders
- H2020 Marie Skłodowska-Curie Actions
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Keywords
- multimodal fusion, video sentiment analysis, quantum-inspired neural networks, quantum entanglement, superposition, complex-valued neural networks, interpretability
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