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Link Prediction On Wn18Rr

Metrics

Hits@1
Hits@10
Hits@3
MR
MRR

Results

Performance results of various models on this benchmark

Model Name
Hits@1
Hits@10
Hits@3
MR
MRR
Paper TitleRepository
DensE0.4430.5790.50830520.491DensE: An Enhanced Non-commutative Representation for Knowledge Graph Embedding with Adaptive Semantic Hierarchy-
SAttLE0.4540.5580.508-0.491Self-attention Presents Low-dimensional Knowledge Graph Embeddings for Link Prediction-
NBFNet0.4970.6660.5736360.551Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction-
RotH0.4490.5860.514-.496Low-Dimensional Hyperbolic Knowledge Graph Embeddings-
HittER0.4620.5840.516-0.503HittER: Hierarchical Transformers for Knowledge Graph Embeddings-
ComplEx-N3 (reciprocal)-0.57--0.48Canonical Tensor Decomposition for Knowledge Base Completion-
NePTuNe0.4550.5570.507-0.491NePTuNe: Neural Powered Tucker Network for Knowledge Graph Completion-
RotatE + GreenKGC (Ours)-0.4910.43-0.411GreenKGC: A Lightweight Knowledge Graph Completion Method-
DistMult (after variational EM)----0.455Augmenting and Tuning Knowledge Graph Embeddings-
LERP0.5930.6820.634-0.622Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning-
ComplEx NSCaching-0.5089-53650.4463NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding-
ConE0.4530.5790.515-0.496Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Cones-
CapsE-0.56-719.00.415A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization-
MoCoSA0.6240.820.737-0.696MoCoSA: Momentum Contrast for Knowledge Graph Completion with Structure-Augmented Pre-trained Language Models-
DRUM (T=3)0.4250.5860.513-0.486DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs-
PALT-0.693-61-PALT: Parameter-Lite Transfer of Language Models for Knowledge Graph Completion-
HAKE0.4520.5820.516-0.497Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction-
LineaRE0.4530.5780.50916440.495LineaRE: Simple but Powerful Knowledge Graph Embedding for Link Prediction-
KGRefiner-0.57-6830.448KGRefiner: Knowledge Graph Refinement for Improving Accuracy of Translational Link Prediction Methods-
DisMult0.39---0.43Embedding Entities and Relations for Learning and Inference in Knowledge Bases-
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Link Prediction On Wn18Rr | SOTA | HyperAI