Papers Multi-modal Entity Alignment
“Multi-modal Entity Alignment” 태그가 달린 논문 21편 · 필터 해제
MyGram: Modality-aware Graph Transformer with Global Distribution for Multi-modal Entity Alignment
Multi-modal entity alignment aims to identify equivalent entities between two multi-modal Knowledge graphs by integrating multi-modal data, such as images and text, to enrich the semantic representations of entities. How…
Multi-modal Entity AlignmentKnowledge GraphsLearning with Dual-level Noisy Correspondence for Multi-modal Entity Alignment
Multi-modal entity alignment (MMEA) aims to identify equivalent entities across heterogeneous multi-modal knowledge graphs (MMKGs), where each entity is described by attributes from various modalities. Existing methods t…
Multi-modal Entity AlignmentKnowledge GraphsMitigating Modality Bias in Multi-modal Entity Alignment from a Causal Perspective
Multi-Modal Entity Alignment (MMEA) aims to retrieve equivalent entities from different Multi-Modal Knowledge Graphs (MMKGs), a critical information retrieval task. Existing studies have explored various fusion paradigms…
counterfactualEntity AlignmentInformation RetrievalKnowledge Graphs+1MCSFF: Multi-modal Consistency and Specificity Fusion Framework for Entity Alignment
Multi-modal entity alignment (MMEA) is essential for enhancing knowledge graphs and improving information retrieval and question-answering systems. Existing methods often focus on integrating modalities through their com…
Entity AlignmentInformation RetrievalKnowledge GraphsManagement+3LoginMEA: Local-to-Global Interaction Network for Multi-modal Entity Alignment
Multi-modal entity alignment (MMEA) aims to identify equivalent entities between two multi-modal knowledge graphs (MMKGs), whose entities can be associated with relational triples and related images. Most previous studie…
Entity AlignmentGraph AttentionKnowledge GraphsMulti-modal Entity AlignmentIBMEA: Exploring Variational Information Bottleneck for Multi-modal Entity Alignment
Multi-modal entity alignment (MMEA) aims to identify equivalent entities between multi-modal knowledge graphs (MMKGs), where the entities can be associated with related images. Most existing studies integrate multi-modal…
Entity AlignmentKnowledge GraphsMulti-modal Entity AlignmentProgressively Modality Freezing for Multi-Modal Entity Alignment
Multi-Modal Entity Alignment aims to discover identical entities across heterogeneous knowledge graphs. While recent studies have delved into fusion paradigms to represent entities holistically, the elimination of featur…
Entity AlignmentKnowledge GraphsMulti-modal Entity AlignmentLeveraging Intra-modal and Inter-modal Interaction for Multi-Modal Entity Alignment
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 differe…
Contrastive LearningEntity AlignmentKnowledge GraphsMulti-modal Entity AlignmentNoise-powered Multi-modal Knowledge Graph Representation Framework
The rise of Multi-modal Pre-training highlights the necessity for a unified Multi-Modal Knowledge Graph (MMKG) representation learning framework. Such a framework is essential for embedding structured knowledge into mult…
Entity AlignmentKnowledge Graph CompletionMisconceptionsMulti-modal Entity Alignment+2Pseudo-Label Calibration Semi-supervised Multi-Modal Entity Alignment
Multi-modal entity alignment (MMEA) aims to identify equivalent entities between two multi-modal knowledge graphs for integration. Unfortunately, prior arts have attempted to improve the interaction and fusion of multi-m…
AttributeContrastive LearningEntity AlignmentKnowledge Graphs+2Towards Semantic Consistency: Dirichlet Energy Driven Robust Multi-Modal Entity Alignment
In Multi-Modal Knowledge Graphs (MMKGs), Multi-Modal Entity Alignment (MMEA) is crucial for identifying identical entities across diverse modal attributes. However, semantic inconsistency, mainly due to missing modal att…
AttributeEntity AlignmentGraph LearningKnowledge Graphs+2Multi-Modal Knowledge Graph Transformer Framework for Multi-Modal Entity Alignment
Multi-Modal Entity Alignment (MMEA) is a critical task that aims to identify equivalent entity pairs across multi-modal knowledge graphs (MMKGs). However, this task faces challenges due to the presence of different types…
Entity AlignmentKnowledge GraphsMulti-modal Entity AlignmentMulti-modal Knowledge GraphUniversal Multi-modal Entity Alignment via Iteratively Fusing Modality Similarity Paths
The objective of Entity Alignment (EA) is to identify equivalent entity pairs from multiple Knowledge Graphs (KGs) and create a more comprehensive and unified KG. The majority of EA methods have primarily focused on the …
Entity AlignmentKnowledge GraphsMulti-modal Entity AlignmentRethinking Uncertainly Missing and Ambiguous Visual Modality in Multi-Modal Entity Alignment
As a crucial extension of entity alignment (EA), multi-modal entity alignment (MMEA) aims to identify identical entities across disparate knowledge graphs (KGs) by exploiting associated visual information. However, exist…
BenchmarkingEntity AlignmentKnowledge Graph EmbeddingsKnowledge Graphs+1Attribute-Consistent Knowledge Graph Representation Learning for Multi-Modal Entity Alignment
The multi-modal entity alignment (MMEA) aims to find all equivalent entity pairs between multi-modal knowledge graphs (MMKGs). Rich attributes and neighboring entities are valuable for the alignment task, but existing wo…
AttributeEntity AlignmentGraph Neural NetworkGraph Representation Learning+4MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybrid
Multi-modal entity alignment (MMEA) aims to discover identical entities across different knowledge graphs (KGs) whose entities are associated with relevant images. However, current MMEA algorithms rely on KG-level modali…
Entity AlignmentKnowledge GraphsMulti-modal Entity AlignmentMulti-modal Contrastive Representation Learning for Entity Alignment
Multi-modal entity alignment aims to identify equivalent entities between two different multi-modal knowledge graphs, which consist of structural triples and images associated with entities. Most previous works focus on …
Contrastive LearningEntity AlignmentKnowledge GraphsMulti-modal Entity Alignment+1Multi-modal Siamese Network for Entity Alignment
The booming of multi-modal knowledge graphs (MMKGs) has raised the imperative demand for multi-modal entity alignment techniques, which facilitate the integration of multiple MMKGs from separate data sources. Unfortunate…
AttributeContrastive LearningEntity AlignmentKnowledge Graphs+2Multi-modal Entity Alignment in Hyperbolic Space
Many AI-related tasks involve the interactions of data in multiple modalities. It has been a new trend to merge multi-modal information into knowledge graph(KG), resulting in multi-modal knowledge graphs (MMKG). However,…
Entity AlignmentKnowledge GraphsMulti-modal Entity AlignmentVisual Pivoting for (Unsupervised) Entity Alignment
This work studies the use of visual semantic representations to align entities in heterogeneous knowledge graphs (KGs). Images are natural components of many existing KGs. By combining visual knowledge with other auxilia…
Entity AlignmentKnowledge GraphsMulti-modal Entity Alignment