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 401425 of 2974 papers

TitleStatusHype
Learning Dynamic Belief Graphs to Generalize on Text-Based GamesCode1
Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation NetworksCode1
Learning Representations for Hyper-Relational Knowledge GraphsCode1
Learning Representations of Bi-level Knowledge Graphs for Reasoning beyond Link PredictionCode1
Learning through structure: towards deep neuromorphic knowledge graph embeddingsCode1
Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge GraphsCode1
Application of Knowledge Graphs to Provide Side Information for Improved Recommendation AccuracyCode1
Fine-tuned LLMs Know More, Hallucinate Less with Few-Shot Sequence-to-Sequence Semantic Parsing over WikidataCode1
KGLiDS: A Platform for Semantic Abstraction, Linking, and Automation of Data ScienceCode1
CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable RecommendationCode1
LKPNR: LLM and KG for Personalized News Recommendation FrameworkCode1
CAKE: A Scalable Commonsense-Aware Framework For Multi-View Knowledge Graph CompletionCode1
Deep Graph Matching ConsensusCode1
Deliberation on Priors: Trustworthy Reasoning of Large Language Models on Knowledge GraphsCode1
Can Knowledge Graphs Simplify Text?Code1
CypherBench: Towards Precise Retrieval over Full-scale Modern Knowledge Graphs in the LLM EraCode1
DDGCN: Dual Dynamic Graph Convolutional Networks for Rumor Detection on Social MediaCode1
MedPix 2.0: A Comprehensive Multimodal Biomedical Data set for Advanced AI ApplicationsCode1
Message Passing for Hyper-Relational Knowledge GraphsCode1
Message Passing Query EmbeddingCode1
CuriousLLM: Elevating Multi-Document QA with Reasoning-Infused Knowledge Graph PromptingCode1
MICO: A Multi-alternative Contrastive Learning Framework for Commonsense Knowledge RepresentationCode1
Complex Query Answering with Neural Link PredictorsCode1
Mixture-of-Partitions: Infusing Large Biomedical Knowledge Graphs into BERTCode1
causalgraph: A Python Package for Modeling, Persisting and Visualizing Causal Graphs Embedded in 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