PCMEA proposes a novel framework for multi-modal entity alignment, addressing challenges like modal-specific noise and limited labeled data. The method combines diverse encoders and attention mechanisms to extract features, filters noise using mutual information maximization, and improves alignment with pseudo-label calibration. Experimental results demonstrate superior performance compared to state-of-the-art methods on two benchmark datasets.
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by Luyao Wang,P... às arxiv.org 03-05-2024
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