Link Prediction On Wn18Rr

Metriken

Hits@1

Hits@10

Hits@3

MRR

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Vergleichstabelle

Modellname	Hits@1	Hits@10	Hits@3	MR	MRR
dense-an-enhanced-non-abelian-group	0.443	0.579	0.508	3052	0.491
self-attention-presents-low-dimensional	0.454	0.558	0.508	-	0.491
neural-bellman-ford-networks-a-general-graph	0.497	0.666	0.573	636	0.551
low-dimensional-hyperbolic-knowledge-graph-1	0.449	0.586	0.514	-	.496
hitter-hierarchical-transformers-for	0.462	0.584	0.516	-	0.503
canonical-tensor-decomposition-for-knowledge	-	0.57	-	-	0.48
neptune-neural-powered-tucker-network-for	0.455	0.557	0.507	-	0.491
greenkgc-a-lightweight-knowledge-graph	-	0.491	0.43	-	0.411
augmenting-and-tuning-knowledge-graph	-	-	-	-	0.455
logical-entity-representation-in-knowledge	0.593	0.682	0.634	-	0.622
nscaching-simple-and-efficient-negative	-	0.5089	-	5365	0.4463
modeling-heterogeneous-hierarchies-with	0.453	0.579	0.515	-	0.496
a-capsule-network-based-embedding-model-for-1	-	0.56	-	719.0	0.415
mocosa-momentum-contrast-for-knowledge-graph	0.624	0.82	0.737	-	0.696
drum-end-to-end-differentiable-rule-mining-on	0.425	0.586	0.513	-	0.486
palt-parameter-lite-transfer-of-language	-	0.693	-	61	-
learning-hierarchy-aware-knowledge-graph	0.452	0.582	0.516	-	0.497
knowledge-graph-embedding-with-linear	0.453	0.578	0.509	1644	0.495
kgrefiner-knowledge-graph-refinement-for	-	0.57	-	683	0.448
embedding-entities-and-relations-for-learning	0.39	-	-	-	0.43
how-does-knowledge-graph-embedding	0.446	0.572	0.509	3211	0.484
unified-interpretation-of-softmax-cross	0.444	0.553	0.496	-	0.481
autokge-searching-scoring-functions-for	-	0.567	-	-	0.490
from-discrimination-to-generation-knowledge	0.287	0.535	0.403	-	-
hypernetwork-knowledge-graph-embeddings	0.436	0.522	0.477	5796	0.465
kg-bert-bert-for-knowledge-graph-completion	-	0.524	-	97	-
decompressing-knowledge-graph-representations	0.427	0.515	0.469	-	0.457
kbgan-adversarial-learning-for-knowledge	-	0.469	-	-	0.215
convolutional-2d-knowledge-graph-embeddings	0.400	0.520	0.440	-	0.430
kermit-knowledge-graph-completion-of-enhanced	0.629	0.832	0.738	-	0.700
quaternion-knowledge-graph-embedding	0.438	0.582	0.508	2314	0.488
multi-partition-embedding-interaction-with	0.444	0.551	0.496	-	0.481
relphormer-relational-graph-transformer-for	0.448	0.591	-	-	0.495
mlmlm-link-prediction-with-mean-likelihood	0.4391	0.611	0.5418	1603	0.5017
knowledge-graph-embedding-via-graph	0.424	0.604	0.525	1270	0.467
probabilistic-case-based-reasoning-for-open	0.43	0.55	0.49	-	0.48
meim-multi-partition-embedding-interaction	0.458	0.577	0.518	-	0.499
unified-interpretation-of-softmax-cross	0.441	0.546	0.491	-	0.477
end-to-end-structure-aware-convolutional	0.43	0.54	0.48	-	0.47
tucker-tensor-factorization-for-knowledge	0.443	0.526	0.482	-	0.470
duality-induced-regularizer-for-tensor	0.441	0.552	-	-	0.478
relation-prediction-as-an-auxiliary-training	0.443	0.578	0.505	-	0.488
rot-pro-modeling-transitivity-by-projection	0.397	0.577	0.482	-	0.457
rotate-knowledge-graph-embedding-by	0.428	0.571	0.492	3340	0.476
quatde-dynamic-quaternion-embedding-for	0.438	0.586	0.509	1977	0.489
greenkgc-a-lightweight-knowledge-graph	0.3	0.413	0.365	-	0.342
composition-based-multi-relational-graph	0.443	0.546	0.494	3533	0.479
safran-an-interpretable-rule-based-link	0.459	0.578	-	-	0.502
language-models-as-knowledge-embeddings	0.523	0.789	0.671	79	0.619
duality-induced-regularizer-for-tensor	0.455	0.577	-	-	0.498
semantic-triple-encoder-for-fast-open-set	0.243	0.709	0.491	51	0.401
embedding-knowledge-graphs-attentive-to	-	0.575	-	3390	0.486
a-novel-embedding-model-for-knowledge-base	-	0.525	-	2554.0	0.248
simkgc-simple-contrastive-knowledge-graph	0.588	0.817	0.731	-	0.671
convolutional-2d-knowledge-graph-embeddings	0.35	0.35	0.35	13526	0.35
m-walk-learning-to-walk-over-graphs-using	0.414	-	0.445	-	0.437
duality-induced-regularizer-for-tensor	0.449	-	-	-	0.491
190600687	0.452	0.557	0.505	-	0.486
rotate-knowledge-graph-embedding-by	0.417	0.552	0.479	2923	0.462
multi-relational-poincare-graph-embeddings	0.440	0.566	0.495	-	0.481
orthogonal-relation-transforms-with-graph	0.442	0.583	0.511	2715	0.491
mde-multi-distance-embeddings-for-link	-	0.560	-	3219	0.458
mocokgc-momentum-contrast-entity-encoding-for	0.665	0.881	0.792	-	0.742
joint-language-semantic-and-structure	-	0.786	-	35	-
complex-embeddings-for-simple-link-prediction	0.410	0.510	-	-	0.440
translating-embeddings-for-modeling-multi	0.4226	0.5555	-	-	0.4659
learning-attention-based-embeddings-for	0.361	0.581	0.483	1940.0	0.44
contextual-parameter-generation-for-knowledge	.4405	.5612	-	-	.4833
predicting-semantic-relations-using-global	0.4537	0.5902	-	-	0.4983
adaptive-convolution-for-multi-relational	0.443	0.537	0.489	-	0.475
self-distillation-with-meta-learning-for-1	0.447	0.570	0.504	-	0.491
lp-bert-multi-task-pre-training-knowledge	0.343	0.752	0.563	92	0.482
interacte-improving-convolution-based	0.430	0.528	-	5202	0.463
kglm-integrating-knowledge-graph-structure-in	0.330	0.741	0.538	40.18	0.467