Hugging Face Trending Papers June 29, 2026

Beyond Triplet Plausibility: Relation Set Completion in Knowledge Graphs

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Knowledge graphs (KGs) organize real-world knowledge as triplets and underpin many downstream applications. Due to their inherent incompleteness, knowledge graph completion (KGC) is widely studied and is typically formulated as triplet prediction, with link prediction as the dominant paradigm.

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arXiv AI

Jun 30

Beyond Triplet Plausibility: Relation Set Completion in Knowledge Graphs

arXiv:2606. 29860v1 Announce Type: new Abstract: Knowledge graphs (KGs) organize real-world knowledge as triplets and underpin many downstream applications.

By Zihao Zheng, Borui Cai, Yao Zhao, Keshav Sood, Yong Xiang

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arXiv:2606. 27967v1 Announce Type: new Abstract: Real-world knowledge graphs are often incomplete, lacking many valid facts.

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By Jiawei Sheng, Taoyu Su, Xixun Lin, Xiaodong Li, Tingwen Liu

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arXiv Machine Learning

Jun 3

Link Prediction or Perdition: the Seeds of Instability in Knowledge Graph Embeddings

arXiv:2606. 03365v1 Announce Type: new Abstract: Embedding models (KGEMs) constitute the main link prediction approach to complete knowledge graphs.

By Guillaume M\'erou\'e, Fabien Gandon, Pierre Monnin

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arXiv Machine Learning

Jun 5

Q-GNN: Query-Conditioned Graph Neural Networks with Type Awareness for Knowledge Graph Completion

arXiv:2606. 05639v1 Announce Type: new Abstract: Knowledge Graph Completion (KGC) aims at predicting missing triplets from incomplete knowledge graphs, which is crucial for downstream applications.

By Dongxiao He, Ruqiong Zhang, Zhizhi Yu, Ling Ding, Di Jin, Guangquan Xu, Zhiyong Feng

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