SOTAVerified

Knowledge Graph Completion

Knowledge graphs $G$ are represented as a collection of triples $\{(h, r, t)\}\subseteq E\times R\times E$, where $E$ and $R$ are the entity set and relation set. The task of Knowledge Graph Completion is to either predict unseen relations $r$ between two existing entities: $(h, ?, t)$ or predict the tail entity $t$ given the head entity and the query relation: $(h, r, ?)$.

Source: One-Shot Relational Learning for Knowledge Graphs

Papers

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Showing 151–200 of 482 papers

TitleStatusHype
Distantly Supervised Biomedical Knowledge Acquisition via Knowledge Graph Based Attention—0
A Pluggable Common Sense-Enhanced Framework for Knowledge Graph Completion—0
Knowledge Reasoning via Jointly Modeling Knowledge Graphs and Soft Rules—0
Discovering Fine-Grained Semantics in Knowledge Graph Relations—0
Automated assessment of knowledge hierarchy evolution: comparing directed acyclic graphs—0
DiffusionCom: Structure-Aware Multimodal Diffusion Model for Multimodal Knowledge Graph Completion—0
Knowledge Graphs: Opportunities and Challenges—0
A Translation-Based Knowledge Graph Embedding Preserving Logical Property of Relations—0
Knowledge Graph Embedding: A Probabilistic Perspective and Generalization Bounds—0
A Topological View of Rule Learning in Knowledge Graphs—0
An Overview of Distant Supervision for Relation Extraction with a Focus on Denoising and Pre-training Methods—0
Knowledge Graph Completion with Text-aided Regularization—0
Knowledge Graph Embedding via Graph Attenuated Attention Networks—0
Decoupling Mixture-of-Graphs: Unseen Relational Learning for Knowledge Graph Completion by Fusing Ontology and Textual Experts—0
Data Collection vs. Knowledge Graph Completion: What is Needed to Improve Coverage?—0
Abstract Graphs and Abstract Paths for Knowledge Graph Completion—0
5* Knowledge Graph Embeddings with Projective Transformations—0
Cyber Knowledge Completion Using Large Language Models—0
Improved Knowledge Graph Embedding using Background Taxonomic Information—0
A Temporal Knowledge Graph Completion Method Based on Balanced Timestamp Distribution—0
Knowledge Graph Completion with Pre-trained Multimodal Transformer and Twins Negative Sampling—0
Knowledge Transfer with Medical Language Embeddings—0
Learning Structured Embeddings of Knowledge Graphs with Adversarial Learning Framework—0
Knowledge Graph Assisted Automatic Sports News Writing—0
Cross-lingual Alignment of Knowledge Graph Triples with Sentences—0
Knowledge Graph Completion as Tensor Decomposition: A Genreal Form and Tensor N-rank Regularization—0
A Contextualized BERT model for Knowledge Graph Completion—0
Knowledge Graph and Text Jointly Embedding—0
Knowledge Graph Completion Method Combined With Adaptive Enhanced Semantic Information—0
History Repeats: Overcoming Catastrophic Forgetting For Event-Centric Temporal Knowledge Graph Completion—0
Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion—0
HDReason: Algorithm-Hardware Codesign for Hyperdimensional Knowledge Graph Reasoning—0
ConvD: Attention Enhanced Dynamic Convolutional Embeddings for Knowledge Graph Completion—0
KGxBoard: Explainable and Interactive Leaderboard for Evaluation of Knowledge Graph Completion Models—0
HyperCausalLP: Causal Link Prediction using Hyper-Relational Knowledge Graph—0
Harmonizing Human Insights and AI Precision: Hand in Hand for Advancing Knowledge Graph Task—0
A Survey on Graph Neural Networks for Knowledge Graph Completion—0
Graph Pattern Entity Ranking Model for Knowledge Graph Completion—0
Contextual Dictionary Lookup for Knowledge Graph Completion—0
IME: Integrating Multi-curvature Shared and Specific Embedding for Temporal Knowledge Graph Completion—0
A*Net and NBFNet Learn Negative Patterns on Knowledge Graphs—0
Knowledge Graph Completion Models are Few-shot Learners: An Empirical Study of Relation Labeling in E-commerce with LLMs—0
Data Augmentation for Few-Shot Knowledge Graph Completion from Hierarchical Perspective—0
Evaluating the Calibration of Knowledge Graph Embeddings for Trustworthy Link Prediction—0
In-Context Learning with Topological Information for Knowledge Graph Completion—0
Incorporating Structured Sentences with Time-enhanced BERT for Fully-inductive Temporal Relation Prediction—0
Context-Enhanced Entity and Relation Embedding for Knowledge Graph Completion—0
INDIGO: GNN-Based Inductive Knowledge Graph Completion Using Pair-Wise Encoding—0
Deep Sparse Latent Feature Models for Knowledge Graph Completion—0
GLTW: Joint Improved Graph Transformer and LLM via Three-Word Language for Knowledge Graph Completion—0
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All datasetsFB15k-237DBP-5L (English)DBP-5L (Greek)DPB-5L (French)WN18RRDBbook2014MovieLens 1M

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1KBGATHits@1062.6—Unverified
2HAKEHits@1054.2—Unverified
3PKGCHits@1048.7—Unverified
4KBATHits@146—Unverified
#ModelMetricClaimedVerifiedStatus
1JMACMRR44.6—Unverified
2AlignKGCMRR41.3—Unverified
3SS-AGAMRR32.1—Unverified
#ModelMetricClaimedVerifiedStatus
1JMACMRR71.7—Unverified
2AlignKGCMRR69.4—Unverified
3SS-AGAMRR35.3—Unverified
#ModelMetricClaimedVerifiedStatus
1JMACMRR64.5—Unverified
2AlignKGCMRR59.5—Unverified
3SS-AGAMRR36.6—Unverified
#ModelMetricClaimedVerifiedStatus
1HAKEHits@30.52—Unverified
2KBGATHits@30.48—Unverified
#ModelMetricClaimedVerifiedStatus
1KTUP (soft)Hits@1060.75—Unverified
#ModelMetricClaimedVerifiedStatus
1KTUP (soft)Hits@1048.9—Unverified