TY - EJOU AU - Li, Huayu AU - Wang, Xiang AU - Luo, Jia AU - He, Xiaotong AU - Zhang, Peiying TI - A Two-Stage Decoupled Matching Network for Multimodal Entity Linking T2 - Computers, Materials \& Continua PY - VL - IS - SN - 1546-2226 AB - Multimodal Entity Linking (MEL) aims to map ambiguous mentions in multimodal contexts to their corresponding entities in a multimodal knowledge base. However, existing methods still face limitations in terms of feature extraction granularity, the depth of cross-modal interaction, and architectural coupling. To address these issues, we propose a Two-stage Decoupled Matching Network (TDMN) for multimodal entity linking. The matching process is divided into two stages: intra-modal matching and cross-modal interaction. In the intra-modal stage, textual and visual inputs are processed independently. The framework then proceeds to the cross-modal interaction stage, following the principle of “enhancement prior to interaction.” Specifically, unimodal features are first refined through a parallel dual-attention network consisting of Global Relational Attention and Adaptive Sharpening Attention, together with a multi-granularity calibration fusion module. Based on the refined representations, cross-modal alignment is subsequently performed within a symmetric bidirectional interaction architecture, in which a gated residual mechanism is introduced to facilitate information fusion. Experiments conducted on the public benchmark datasets WikiMEL and WikiDiverse demonstrate the effectiveness of TDMN. Compared with the M3EL baseline, TDMN achieves absolute improvements of 1.39% and 1.88% in MRR and Hits@1, respectively, on the WikiDiverse dataset. In addition, compared with MIMIC, TDMN improves MRR and Hits@1 by 0.8% and 1.21%, respectively, on the WikiMEL dataset. These results support the effectiveness of the proposed approach. KW - Multimodal entity linking; multi-granularity feature fusion; attention mechanism; feature enhancement; multimodal representation learning DO - 10.32604/cmc.2026.085456