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 21262150 of 2974 papers

TitleStatusHype
Ontology Population using LLMs0
Auto-Encoding User Ratings via Knowledge Graphs in Recommendation Scenarios0
A Universal Knowledge Model and Cognitive Architecture for Prototyping AGI0
A Unified Knowledge Graph Augmentation Service for Boosting Domain-specific NLP Tasks0
OpenAg: Democratizing Agricultural Intelligence0
AUGUST: an Automatic Generation Understudy for Synthesizing Conversational Recommendation Datasets0
OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs0
Open-domain Dialogue Generation Grounded with Dynamic Multi-form Knowledge Fusion0
Open-domain Factoid Question Answering via Knowledge Graph Search0
Open-Domain Question Answering with Pre-Constructed Question Spaces0
Augmenting Topic Aware Knowledge-Grounded Conversations with Dynamic Built Knowledge Graphs0
Towards Time-Aware Knowledge Graph Completion0
Open Research Knowledge Graph: Next Generation Infrastructure for Semantic Scholarly Knowledge0
Towards Trustworthy Knowledge Graph Reasoning: An Uncertainty Aware Perspective0
Towards Understanding the Evolution of Vocabulary Terms in Knowledge Graphs0
Open-World Visual Recognition Using Knowledge Graphs0
OpticE: A Coherence Theory-Based Model for Link Prediction0
Zero-Shot Fact-Checking with Semantic Triples and Knowledge Graphs0
Optimization of Retrieval Algorithms on Large Scale Knowledge Graphs0
Optimizing the Interface Between Knowledge Graphs and LLMs for Complex Reasoning0
Order Matters: Matching Multiple Knowledge Graphs0
Toward the Automated Construction of Probabilistic Knowledge Graphs for the Maritime Domain0
Toward Understanding The Effect of Loss Function on The Performance of Knowledge Graph Embedding0
Augmenting Knowledge Graph Hierarchies Using Neural Transformers0
Augmenting Compositional Models for Knowledge Base Completion Using Gradient Representations0
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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