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DERA: Dense Entity Retrieval for Entity Alignment in Knowledge Graphs

arXiv 2408.01154 ↗First posted 2 Aug 2024cs.CL cs.AIcited by 0

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Abstract (arXiv)

Entity Alignment (EA) aims to match equivalent entities in different Knowledge Graphs (KGs), which is essential for knowledge fusion and integration. Recently, embedding-based EA has attracted significant attention and many approaches have been proposed. Early approaches primarily focus on learning entity embeddings from the structural features of KGs, defined by relation triples. Later methods incorporated entities' names and attributes as auxiliary information to enhance embeddings for EA. However, these approaches often used different techniques to encode structural and attribute information, limiting their interaction and mutual enhancement. In this work, we propose a dense entity retrieval framework for EA, leveraging language models to uniformly encode various features of entities and facilitate nearest entity search across KGs. Alignment candidates are first generated through entity retrieval, which are subsequently reranked to determine the final alignments. We conduct comprehensive experiments on both cross-lingual and monolingual EA datasets, demonstrating that our approach achieves state-of-the-art performance compared to existing EA methods.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 29 of its 47 references that are in the map. First posted on arXiv 2 Aug 2024.

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References · 29

  1. 2023FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioningcited by 2,551
  2. 2019ZeRO: Memory Optimizations Toward Training Trillion Parameter Modelscited by 1,278
  3. 2024M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillationcited by 1,050
  4. 2016Training Deep Nets with Sublinear Memory Costcited by 825
  5. 2016Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignmentcited by 128
  6. 2017Cross-lingual Entity Alignment via Joint Attribute-Preserving Embeddingcited by 126
  7. 2020A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphscited by 119
  8. 2019Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphscited by 106
  9. 2019Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregationcited by 101
  10. 2019Multi-Channel Graph Neural Network for Entity Alignmentcited by 86
  11. 2019Learning to Exploit Long-term Relational Dependencies in Knowledge Graphscited by 83
  12. 2019Multi-view Knowledge Graph Embedding for Entity Alignmentcited by 74
17 more
  1. 2019Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Networkcited by 68
  2. 2019Aligning Cross-Lingual Entities with Multi-Aspect Informationcited by 46
  3. 2020Neighborhood Matching Network for Entity Alignmentcited by 44
  4. 2019Jointly Learning Entity and Relation Representations for Entity Alignmentcited by 39
  5. 2022SelfKG: Self-Supervised Entity Alignment in Knowledge Graphscited by 32
  6. 2019Collective Entity Alignment via Adaptive Featurescited by 30
  7. 2021From Alignment to Assignment: Frustratingly Simple Unsupervised Entity Alignmentcited by 26
  8. 2019JarKA: Modeling Attribute Interactions for Cross-lingual Knowledge Alignmentcited by 19
  9. 2021Unsupervised Knowledge Graph Alignment by Probabilistic Reasoning and Semantic Embeddingcited by 18
  10. 2022LightEA: A Scalable, Robust, and Interpretable Entity Alignment Framework via Three-view Label Propagationcited by 18
  11. 2023A Fused Gromov-Wasserstein Framework for Unsupervised Knowledge Graph Entity Alignmentcited by 16
  12. 2023Toward Practical Entity Alignment Method Design: Insights from New Highly Heterogeneous Knowledge Graph Datasetscited by 8
  13. 2024Two Heads Are Better Than One: Integrating Knowledge from Knowledge Graphs and Large Language Models for Entity Alignmentcited by 8
  14. 2022Interactive Contrastive Learning for Self-supervised Entity Alignmentcited by 7
  15. 2022An Accurate Unsupervised Method for Joint Entity Alignment and Dangling Entity Detectioncited by 7
  16. 2023From Alignment to Entailment: A Unified Textual Entailment Framework for Entity Alignmentcited by 6
  17. 2022Conflict-Aware Pseudo Labeling via Optimal Transport for Entity Alignmentcited by 5

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  1. 2024LLM-Align: Utilizing Large Language Models for Entity Alignment in Knowledge Graphs
  2. 2026HELEA: Hard-Negative Benchmark and LLM-based Reranking for Robust Entity Alignment
  3. 2026Predicate Importance Estimation and Decoupled Rationale-Score Distillation for Entity Alignment
  4. 2023AutoAlign: Fully Automatic and Effective Knowledge Graph Alignment enabled by Large Language Models
  5. 2024Entity Alignment with Noisy Annotations from Large Language Models
  6. 2024Unlocking the Power of Large Language Models for Entity Alignment
  7. 2025SlimRAG: Retrieval without Graphs via Entity-Aware Context Selection
  8. 2025KGMEL: Knowledge Graph-Enhanced Multimodal Entity Linking