Quantum-inspired multimodal fusion for video sentiment analysis

Attention Is All You Need

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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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XLNet: Generalized Autoregressive Pretraining for Language Understanding

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The Mythos of Model Interpretability: In machine learning, the concept of interpretability is both important and slippery.

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Quantum Computation and Quantum Information: 10th Anniversary Edition

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Multimodal Transformer for Unaligned Multimodal Language Sequences

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Tensor Fusion Network for Multimodal Sentiment Analysis

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Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

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Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph

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Representation models and processing operators for quantum informational multi-media

Li, Y. (2025) · PLoS ONE · doi:10.1371/journal.pone.0313294 · Cited by 2

Quantum-inspired multimodal fusion with Lindblad master equation for sentiment analysis

Yan, K., Lai, P., Yang, Y., Ren, Y., Badarch, T., Chen, Y., & Zheng, X. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.130710 · Cited by 3

A multi-view and multi-granularity emotional semantic interaction framework combining graph and attention mechanism for multimodal sentiment analysis

Li, Z., Guo, X., Wu, H., Yu, J., Chen, H., Gao, Y., Huang, X., & Pan, Y. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.131380 · Cited by 2

Quantum Interference-Inspired Who-What-Where Composite-Semantics Instance Search for Story Videos

Xu, Z., Guo, J., Zhang, C., Wang, Z., Xiao, C., & Liang, C. (2025) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3746027.3755325 · Cited by 2

A comprehensive review on quantum steganography techniques for data hiding

Patra, A., Barik, R. C., & Changder, S. (2026) · Computer Science Review · doi:10.1016/j.cosrev.2026.100911 · Cited by 2

A quantum-cognitive approach to dynamic meaning construction

Yin, M. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1664747 · Cited by 2

Recent Advancements and Challenges in Multimodal Sentiment Analysis: A Survey

Dong, Z.-X., & Liu, H. (2023) · International Conference on Machine Learning and Cybernetics · doi:10.1109/icmlc58545.2023.10327944 · Cited by 2

Comparison of Machine Learning Text Classification for Intent Sentiment Analysis

Muhammad, A., Defit, S., & Nurcahyo, G. W. (2023) · International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) · doi:10.1109/icitisee58992.2023.10405200 · Cited by 2

Toward Domain Adaptive Learning-Based Variation Autoencoder Emotional Analysis in English Teaching

Wang, X. (2024) · International Journal of Artificial Intelligence Tools · doi:10.1142/s0218213024400062 · Cited by 2

Machine Learning Based Multimodal Opinion Mining

Sharma, R., Shah, H., Jain, D., & Shah, B. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-97-8666-4_23 · Cited by 2

Maximizing Sentiment Detection Through Comprehensive Multimodal Data Fusion: Integrating CNN, RNN, LSTM

Kavitha., A., Aishwarya, B., & Durgagowri, G. (2025) · International Conference on Multi-Agent Systems for Collaborative Intelligence (ICMSCI) · doi:10.1109/icmsci62561.2025.10894282 · Cited by 2

Intrusion Detection Systems Using Quantum-Inspired Density Matrix Encodings

Huynh, L., Hong, J. B., Mian, A. S., Suzuki, H., & Camtepe, S. A. (2024) · International Conference on Dependable Systems and Networks workshops · doi:10.1109/dsn-w60302.2024.00019 · Cited by 1

Cross-Modality Disentangled Information Bottleneck Strategy for Multimodal Sentiment Analysis

Deng, Z., Huang, G., Zhong, G., Yuan, X., Huang, L., & Pun, C. (2024) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc54092.2024.10831481 · Cited by 1

Quantum-Enhanced Social Robotics: The QUADRI Project

Carolis, B. N. D., Loglisci, C. A. A. M. D., Miccoli, M. G., Palestra, G., & Violante, S. (2025) · ACM Conference on User Modeling, Adaptation and Personalization (UMAP) · doi:10.1145/3708319.3735545 · Cited by 1

Exploring Feature Interactions for Multimodal Sentiment Analysis

Xu, D., & Zhang, C. (2025) · International Journal of Cognitive Informatics and Natural Intelligence · doi:10.4018/ijcini.383754 · Cited by 1

CR-GAC: Cross-modal Recombination via Graph-Attention Collaborative Optimization for multimodal sentiment analysis

Chen, H., Liu, J., Li, Z., Pan, Y., Tao, H., Wu, H., Wang, Y., & Yang, C. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.129805 · Cited by 1

Kernel density matrices for probabilistic deep learning

Gonzalez, F. A., Ramos-Pollán, R., & Gallego-Mejia, J. A. (2025) · Quantum Machine Intelligence · doi:10.1007/s42484-025-00299-9 · Cited by 1

A dual-modality deep learning approach for fine-grained sentiment analysis using speech and text

Agrawal, D., Deshmukh, M., & Singh, S. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.115141 · Cited by 1

Unsupervised multimodal graph completion networks with multi-level contrastiveness for modality-missing conversation understanding

Fu, S., Peng, S., Zou, B., Jing, X., Yu, W., Peng, Q., & You, X. (2026) · Information Fusion · doi:10.1016/j.inffus.2026.104197 · Cited by 1

Quantifying emotions through quantum computations

Singh, J., & Bhangu, K. S. (2023) · International Journal of Quantum Information · doi:10.1142/s0219749923500041 · Cited by 1

Tree-Based Mix-Order Polynomial Fusion Network for Multimodal Sentiment Analysis

Tang, J., Hou, M., Jin, X., Zhang, J., Zhao, Q., & Kong, W. (2023) · Systems · doi:10.3390/systems11010044 · Cited by 1

Research on the application of English short essay reading emotional analysis in online English teaching under IoT scenario

Zhan, X. (2024) · Internet Technology Letters · doi:10.1002/itl2.535 · Cited by 1

Adaptive Language-Interacted Hyper-Modality Representation for Multimodal Sentiment Analysis

Pan, L., & Liu, W. (2024) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2024.0150746 · Cited by 2

An Intelligent Decision Framework For Facial Expression Recognition Based On Deep LearningPreprint

Pan, X. (2023) · Research Square · doi:10.21203/rs.3.rs-2415620/v1

Multi-modal emotion recognition based on gated composite network

Li, Z., & Jiang, Y. (2023) · International Conference on Cloud Computing, Big Data Application and Software Engineering (CBASE) · doi:10.1109/cbase60015.2023.10439126

Reviewing the past enables us to learn

Zheng, W., & Wang, F. (2024) · Elsevier eBooks · doi:10.1016/b978-0-44-321619-0.00008-x

Quantum-Inspired Fusion for Open-Domain Question Answering

Duan, R., Liu, X., Ding, Z., & Zhang, Y. (2024) · Electronics · doi:10.3390/electronics13204135

A Context-Aware Movie Recommender System Through Semantic Analysis and Visual Comprehension-Driven Multimodal Fusion

Yuan, L., & He, M. (2024) · Journal of Circuits Systems and Computers · doi:10.1142/s021812662550183x

Decoding Sentiments: An Efficient Trans-Long Short Term Memory to Understand Viewer Reactions on Ad-Supported Video Contents

Ramagundam, S., & Karne, N. (2024) · IEEE International Conference on Blockchain and Distributed Systems Security (ICBDS) · doi:10.1109/icbds61829.2024.10837427

A Hierarchical Attention-Based Fusion Model for Multimodal Sentiment Analysis of Customer-Generated Review Videos

Kadu, S., & Joshi, B. (2025) · Vietnam Journal of Computer Science · doi:10.1142/s2196888825500228

MDR-MSA: multi-perspective decoupled representation learning for multimodal sentiment analysis

Du, J., Zhi, Y., Wang, H., Wang, K., & Li, J. (2025) · Multimedia Systems · doi:10.1007/s00530-025-02062-3 · Cited by 1

Text-driven Noise Filtering and Affective Conflict Mitigation Network for Multimodal Sentiment Analysis

Chen, Z., Zhong, H., Alhusaini, N., & Chen, G. (2025) · International Conference on Networking and Network Applications (NaNA) · doi:10.1109/nana66698.2025.00066

Exploring Quantum-Inspired Encoding Strategies in Neuromorphic Systems for Affective State Recognition

Wang, F., Liang, X., & Du, X. (2026) · Sensors · doi:10.3390/s26020568

Unimodal Feature Refinement and Gated Fusion Mechanisms for Multimodal Sentiment Analysis*

Zhao, J., Yu, C., Zheng, J., & Fu, H. (2025) · IEEE International Conference on Frontiers Technology of Information and Computer (ICFTIC) · doi:10.1109/icftic68075.2025.11324730

OPAL-T: Order-Insensitive Prototype-Aware Low-Rank Trimodal Fusion for Multimodal Sentiment AnalysisPreprint

gao, R., Huang, D., Zhang, G., & Yu, J. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6502094

QMF-MAP: A quantum multimodal fusion model for molecular activity prediction

Li, M., Liu, W., Shi, L., Li, Y., Chen, K., & Zhang, P. (2026) · Information Fusion · doi:10.1016/j.inffus.2026.104584

Representational efficiency and noise robustness in hybrid quantum-classical graph neural networks

Santo, I. A., Bannah, H., Nabi, M. S., & Karim, H. B. A. (2026) · Discover Quantum Science · doi:10.1007/s44464-026-00025-9

A Quantum-Inspired Residual Self-Attention Network for Multimodal Sentiment Analysis

Liu, Y., Feng, X., & Zhong, Y. (2026) · Entropy · doi:10.3390/e28091014

QENN: A Quantum Entanglement-Inspired Neural Network for Interaction and Relationship Prediction in Story Videos

Xu, Z., Wu, Z., Zhang, C., Wang, Z., Xiao, C., & Liang, C. (2026) · doi:10.1109/cvprf71909.2026.00792

Quantum single-image super resolution

Gohel, P., & Joshi, M. (2026) · Quantum Information Processing · doi:10.1007/s11128-026-05357-0

Order-routed fusion with gate-aware prototype contrast for multimodal sentiment analysis

Li, W., & Zhang, P. (2026) · Expert Systems with Applications · doi:10.1016/j.eswa.2026.134799

An Entanglement-driven Fusion Neural Network for Video Sentiment Analysis

Gkoumas, D., Li, Q., Yu, Y., & Song, D. (2021) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2021/239 · Cited by 15

A quantum-inspired multimodal sentiment analysis framework

Zhang, Y., Song, D., Zhang, P., Wang, P., Li, J., Li, X., & Wang, B. (2018) · Theoretical Computer Science · doi:10.1016/j.tcs.2018.04.029 · Cited by 107

Towards Multimodal Sentiment Analysis Inspired by the Quantum Theoretical Framework

Li, Q., Stefani, A., Toto, G., Buccio, E. D., & Melucci, M. (2020) · IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR) · doi:10.1109/mipr49039.2020.00044 · Cited by 4

Quantum Cognitively Motivated Context-Aware Multimodal Representation Learning for Human Language Analysis

Gkoumas, D. (2021) · Open Research Online (The Open University) · doi:10.21954/ou.ro.00012a25 · Cited by 2

Quantum Cognitively Motivated Decision Fusion for Video Sentiment Analysis

Gkoumas, D., Li, Q., Dehdashti, S., Melucci, M., Yu, Y., & Song, D. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i1.16165 · Cited by 34