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Open AccessArticle
MGMR-Net: Mamba-Guided Multimodal Reconstruction and Fusion Network for Sentiment Analysis with Incomplete Modalities
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School of Computer Science and Engineering, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau 999078, China
2
College of Artificial Intelligence, Zhongkai University of Agriculture and Engineering, Zhongkai Road 501, Guangzhou 510225, China
*
Authors to whom correspondence should be addressed.
Electronics 2025, 14(15), 3088; https://doi.org/10.3390/electronics14153088 (registering DOI)
Submission received: 3 July 2025
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Revised: 21 July 2025
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Accepted: 31 July 2025
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Published: 1 August 2025
Abstract
Multimodal sentiment analysis (MSA) faces key challenges such as incomplete modality inputs, long-range temporal dependencies, and suboptimal fusion strategies. To address these, we propose MGMR-Net, a Mamba-guided multimodal reconstruction and fusion network that integrates modality-aware reconstruction with text-centric fusion within an efficient state-space modeling framework. MGMR-Net consists of two core components: the Mamba-collaborative fusion module, which utilizes a two-stage selective state-space mechanism for fine-grained cross-modal alignment and hierarchical temporal integration, and the Mamba-enhanced reconstruction module, which employs continuous-time recurrence and dynamic gating to accurately recover corrupted or missing modality features. The entire network is jointly optimized via a unified multi-task loss, enabling simultaneous learning of discriminative features for sentiment prediction and reconstructive features for modality recovery. Extensive experiments on CMU-MOSI, CMU-MOSEI, and CH-SIMS datasets demonstrate that MGMR-Net consistently outperforms several baseline methods under both complete and missing modality settings, achieving superior accuracy, robustness, and generalization.
Share and Cite
MDPI and ACS Style
Yang, C.; Liang, Z.; Liu, T.; Hu, Z.; Yan, D.
MGMR-Net: Mamba-Guided Multimodal Reconstruction and Fusion Network for Sentiment Analysis with Incomplete Modalities. Electronics 2025, 14, 3088.
https://doi.org/10.3390/electronics14153088
AMA Style
Yang C, Liang Z, Liu T, Hu Z, Yan D.
MGMR-Net: Mamba-Guided Multimodal Reconstruction and Fusion Network for Sentiment Analysis with Incomplete Modalities. Electronics. 2025; 14(15):3088.
https://doi.org/10.3390/electronics14153088
Chicago/Turabian Style
Yang, Chengcheng, Zhiyao Liang, Tonglai Liu, Zeng Hu, and Dashun Yan.
2025. "MGMR-Net: Mamba-Guided Multimodal Reconstruction and Fusion Network for Sentiment Analysis with Incomplete Modalities" Electronics 14, no. 15: 3088.
https://doi.org/10.3390/electronics14153088
APA Style
Yang, C., Liang, Z., Liu, T., Hu, Z., & Yan, D.
(2025). MGMR-Net: Mamba-Guided Multimodal Reconstruction and Fusion Network for Sentiment Analysis with Incomplete Modalities. Electronics, 14(15), 3088.
https://doi.org/10.3390/electronics14153088
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