Hu, Zhiwei, Gutiérrez-Basulto, Víctor  ORCID: https://orcid.org/0000-0002-6117-5459, Xiang, Zhiliang ORCID: https://orcid.org/0000-0002-0263-7289, Li, Ru and Pan, Jeff Z.
2026.
Leveraging intra-modal and inter-modal interaction for multi-modal entity alignment.
Neurocomputing
676
, 133017.
10.1016/j.neucom.2026.133017
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Abstract
Multi-modal entity alignment (MMEA) aims to identify equivalent entity pairs across different multi-modal knowledge graphs (MMKGs). Existing approaches focus on how to better encode and aggregate information from different modalities. However, it is not trivial to leverage multi-modal knowledge in entity alignment due to the modal heterogeneity. In this paper, we propose a Multi-Grained Interaction framework for Multi-Modal Entity Alignment (MIMEA), which effectively realizes multi-granular interaction within the same modality or between different modalities. MIMEA is composed of four modules: i) a Multi-modal Knowledge Embedding module, which extracts modality-specific representations with multiple individual encoders; ii) a Probability-guided Modal Fusion module, which employs a probability guided approach to integrate uni-modal representations into joint-modal embeddings, while considering the interaction between uni-modal representations; iii) an Optimal Transport Modal Alignment module, which introduces an optimal transport mechanism to encourage the interaction between uni-modal and joint-modal embeddings; iv) a Modal-adaptive Contrastive Learning module, which distinguishes the embeddings of equivalent entities from those of non-equivalent ones, for each modality. Extensive experiments conducted on two real-world datasets demonstrate the strong performance of MIMEA compared to the SoTA. Datasets and code are available at the following website: https://github.com/zhiweihu1103/MEA-MIMEA.
| Item Type: | Article |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Computer Science & Informatics |
| Additional Information: | License information from Publisher: LICENSE 1: Title: This article is under embargo with an end date yet to be finalised. |
| Publisher: | Elsevier |
| ISSN: | 0925-2312 |
| Date of Acceptance: | 6 February 2026 |
| Last Modified: | 20 Feb 2026 10:00 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/185081 |
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