SOTAVerified

Knowledge Graphs

A knowledge graph is a structured representation of information that organizes data into nodes (entities) and edges (relationships) to show how different pieces of knowledge are interconnected. It enables enhanced data integration, search, and inference by modeling the relationships between concepts and entities in a graph format.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1576–1600 of 2974 papers

TitleStatusHype
Modeling Relational Patterns for Logical Query Answering over Knowledge Graphs—0
Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation—0
Modeling Spoken Information Queries for Virtual Assistants: Open Problems, Challenges and Opportunities—0
Modeling the evolution of temporal knowledge graphs with uncertainty—0
Modelling Multi-relations for Convolutional-based Knowledge Graph Embedding—0
Modularized Transfer Learning with Multiple Knowledge Graphs for Zero-shot Commonsense Reasoning—0
Modularized Transfer Learning with Multiple Knowledge Graphs for Zero-shot Commonsense Reasoning—0
ModulE: Module Embedding for Knowledge Graphs—0
MOHONE: Modeling Higher Order Network Effects in KnowledgeGraphs via Network Infused Embeddings—0
Motif Learning in Knowledge Graphs Using Trajectories Of Differential Equations—0
Context Graph—0
MP2D: An Automated Topic Shift Dialogue Generation Framework Leveraging Knowledge Graphs—0
MPRM: A Markov Path-based Rule Miner for Efficient and Interpretable Knowledge Graph Reasoning—0
MRC-based Nested Medical NER with Co-prediction and Adaptive Pre-training—0
MuCo-KGC: Multi-Context-Aware Knowledge Graph Completion—0
MulDE: Multi-teacher Knowledge Distillation for Low-dimensional Knowledge Graph Embeddings—0
Multi-Document Financial Question Answering using LLMs—0
Multi-domain Knowledge Graph Collaborative Pre-training and Prompt Tuning for Diverse Downstream Tasks—0
Multi-hop Commonsense Knowledge Injection Framework for Zero-Shot Commonsense Question Answering—0
Multi-hop Inference for Sentence-level TextGraphs: How Challenging is Meaningfully Combining Information for Science Question Answering?—0
Multi-hop Question Answering over Knowledge Graphs using Large Language Models—0
Multilingual Vector Representations of Words, Sentences, and Documents—0
Multi-Modal Bayesian Embeddings for Learning Social Knowledge Graphs—0
Multi-modal Entity Alignment in Hyperbolic Space—0
Multi-modal Integration Analysis of Alzheimer's Disease Using Large Language Models and Knowledge Graphs—0
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All datasetsMARS (Multimodal Analogical Reasoning dataSet)JerichoWorldWikiKG90M-LSCFB15k

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MarT_MKGformerMRR0.34—Unverified
2MKGformerMRR0.32—Unverified
3MarT_FLAVAMRR0.29—Unverified
4ViLBERTMRR0.29—Unverified
5IKRL (ANALOGY)MRR0.28—Unverified
6IKRLMRR0.27—Unverified
7ViLTMRR0.26—Unverified
8TransAEMRR0.22—Unverified
#ModelMetricClaimedVerifiedStatus
1WorldformerSet accuracy39.15—Unverified
2Q*BERTSet accuracy32.78—Unverified
3GATA-WSet accuracy24.06—Unverified
4WorldformerSet accuracy23.22—Unverified
5Seq2SeqSet accuracy14.29—Unverified
6RulesSet accuracy4.7—Unverified
#ModelMetricClaimedVerifiedStatus
1TransE-ConcatTest MRR85.48—Unverified
2ComplEx-ConcatTest MRR0.86—Unverified
3ComplEx-RoBERTaTest MRR0.72—Unverified
4TransE-RoBERTaTest MRR0.63—Unverified
#ModelMetricClaimedVerifiedStatus
1COMPLEXMRR0.59—Unverified