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

Showing 476500 of 2974 papers

TitleStatusHype
CSKG: The CommonSense Knowledge GraphCode1
A Generalization of Transformer Networks to GraphsCode1
Communicative Message Passing for Inductive Relation ReasoningCode1
Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation NetworksCode1
Keyword-Guided Neural Conversational ModelCode1
Relation-Aware Neighborhood Matching Model for Entity AlignmentCode1
Fork or Fail: Cycle-Consistent Training with Many-to-One MappingsCode1
Scalable and interpretable rule-based link prediction for large heterogeneous knowledge graphsCode1
Fusing Context Into Knowledge Graph for Commonsense Question AnsweringCode1
Open Knowledge Graphs Canonicalization using Variational AutoencodersCode1
Multi-Task Learning for Knowledge Graph Completion with Pre-trained Language ModelsCode1
GenWiki: A Dataset of 1.3 Million Content-Sharing Text and Graphs for Unsupervised Graph-to-Text GenerationCode1
Entity Alignment for Knowledge Graphs with Multi-order Convolutional NetworksCode1
Complex Query Answering with Neural Link PredictorsCode1
CODER: Knowledge infused cross-lingual medical term embedding for term normalizationCode1
A Critical Assessment of State-of-the-Art in Entity AlignmentCode1
CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable RecommendationCode1
Generating Knowledge Graphs by Employing Natural Language Processing and Machine Learning Techniques within the Scholarly DomainCode1
Pre-training Text-to-Text Transformers for Concept-centric Common SenseCode1
Learning Contextualized Knowledge Structures for Commonsense ReasoningCode1
FedE: Embedding Knowledge Graphs in Federated SettingCode1
Language Models are Open Knowledge GraphsCode1
An Industry Evaluation of Embedding-based Entity AlignmentCode1
Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge GraphsCode1
COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge GraphsCode1
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Benchmark Results

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