Knowledge Graphs
968 papers with code • 3 benchmarks • 41 datasets
Benchmarks
These leaderboards are used to track progress in Knowledge Graphs
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Libraries
Use these libraries to find Knowledge Graphs models and implementationsDatasets
ConceptNet
FB15k
ATOMIC
CORD-19
ReDial
Semantic Scholar
MetaQA
DBP15K
ComplexWebQuestions
Jericho
Subtasks
Latest papers
The Integration of Semantic and Structural Knowledge in Knowledge Graph Entity Typing
The Knowledge Graph Entity Typing (KGET) task aims to predict missing type annotations for entities in knowledge graphs.
Zero-shot Logical Query Reasoning on any Knowledge Graph
Complex logical query answering (CLQA) in knowledge graphs (KGs) goes beyond simple KG completion and aims at answering compositional queries comprised of multiple projections and logical operations.
Knowledge graphs for empirical concept retrieval
Concept-based explainable AI is promising as a tool to improve the understanding of complex models at the premises of a given user, viz.\ as a tool for personalized explainability.
BanglaAutoKG: Automatic Bangla Knowledge Graph Construction with Semantic Neural Graph Filtering
Knowledge Graphs (KGs) have proven essential in information processing and reasoning applications because they link related entities and give context-rich information, supporting efficient information retrieval and knowledge discovery; presenting information flow in a very effective manner.
Does Knowledge Graph Really Matter for Recommender Systems?
We consider the scenarios where knowledge in a KG gets completely removed, randomly distorted and decreased, and also where recommendations are for cold-start users.
Rematch: Robust and Efficient Matching of Local Knowledge Graphs to Improve Structural and Semantic Similarity
Knowledge graphs play a pivotal role in various applications, such as question-answering and fact-checking.
An RML-FNML module for Python user-defined functions in Morph-KGC
The RML mapping language declares schema transformations to map heterogeneous data into knowledge graphs.
Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphs
xz-liu/grapheval
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In this paper, we propose GraphEval to evaluate an LLM's performance using a substantially large test dataset.
EventGround: Narrative Reasoning by Grounding to Eventuality-centric Knowledge Graphs
hkust-knowcomp/eventground
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In this work, we propose an initial comprehensive framework called EventGround, which aims to tackle the problem of grounding free-texts to eventuality-centric KGs for contextualized narrative reasoning.
KGUF: Simple Knowledge-aware Graph-based Recommender with User-based Semantic Features Filtering
sisinflab/kguf
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The recent integration of Graph Neural Networks (GNNs) into recommendation has led to a novel family of Collaborative Filtering (CF) approaches, namely Graph Collaborative Filtering (GCF).
