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 1676–1700 of 2974 papers

TitleStatusHype
Collaborative Knowledge Graph Fusion by Exploiting the Open Corpus—0
CogALex-V Shared Task: GHHH - Detecting Semantic Relations via Word Embeddings—0
Co-embedding of Nodes and Edges with Graph Neural Networks—0
LEMON: LanguagE ModeL for Negative Sampling of Knowledge Graph Embeddings—0
Language Model-Guided Knowledge Subgraphs for Question Answering—0
COCO-EX: A Tool for Linking Concepts from Texts to ConceptNet—0
Language Models sounds the Death Knell of Knowledge Graphs—0
Large Knowledge Model: Perspectives and Challenges—0
Large Language Models and Knowledge Graphs: Opportunities and Challenges—0
Large Language Models and Knowledge Graphs for Astronomical Entity Disambiguation—0
Large Language Models as a Tool for Mining Object Knowledge—0
VEM^2L: A Plug-and-play Framework for Fusing Text and Structure Knowledge on Sparse Knowledge Graph Completion—0
Large Language Models for Biomedical Knowledge Graph Construction: Information extraction from EMR notes—0
Large Language Models, Knowledge Graphs and Search Engines: A Crossroads for Answering Users' Questions—0
Large Language Models Meet Knowledge Graphs to Answer Factoid Questions—0
Coarse-to-fine Knowledge Graph Domain Adaptation based on Distantly-supervised Iterative Training—0
Large-Scale Knowledge Synthesis and Complex Information Retrieval from Biomedical Documents—0
Text Classification Based on Knowledge Graphs and Improved Attention Mechanism—0
LEAPME: Learning-based Property Matching with Embeddings—0
CN-HIT-IT.NLP at SemEval-2020 Task 4: Enhanced Language Representation with Multiple Knowledge Triples—0
A Graph-Based Synthetic Data Pipeline for Scaling High-Quality Reasoning Instructions—0
Learning Attention-based Representations from Multiple Patterns for Relation Prediction in Knowledge Graphs—0
Learning Better Word Embedding by Asymmetric Low-Rank Projection of Knowledge Graph—0
Learning beyond datasets: Knowledge Graph Augmented Neural Networks for Natural language Processing—0
Learning Complete Topology-Aware Correlations Between Relations for Inductive Link Prediction—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