Papers with Multimodal entity alignment

2 papers
MM-ChatAlign: A Novel Multimodal Reasoning Framework based on Large Language Models for Entity Alignment (2024.findings-emnlp)

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Challenge: Existing MMEA methods rely on knowledge representation learning (KRL) to measure the similarity of entity embeddings.
Approach: They propose a framework that utilizes the visual reasoning abilities of MLLMs for multimodal entity alignment.
Outcome: The proposed framework integrates the visual reasoning abilities of MLLMs for multimodal entity alignment.
Capturing Latent Modal Association For Multimodal Entity Alignment (2025.findings-emnlp)

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Challenge: Existing methods for multimodal entity alignment overlook the quality of input modality embeddings during modality interaction, amplifying noise propagation while suppressing discriminative feature representations.
Approach: They propose a model for capturing latent modal association for multimodal entity alignment using a self-attention mechanism to enhance salient information while attenuating noise within individual modality embeddings.
Outcome: The proposed model achieves an absolute 3.1% higher Hits@1 score than the sota method.

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