A collection of research on knowledge graphs

Dynamic (Temporal) Knowledge Graph Completion (Reasoning)

TypeDB-ML is the Machine Learning integrations library for TypeDB

LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities

[Tool] For Knowledge Graph Representation Learning

Datasets for Knowledge Graph Completion with textual information about the entities

Implementations of Embedding-based methods for Knowledge Base Completion tasks

The code of paper Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction. Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, Jie Wang. AAAI 2020.

[Paper][AAAI 2025] (MyGO)Tokenization, Fusion, and Augmentation: Towards Fine-grained Multi-modal Entity Representation

A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network (NAACL 2018) (Pytorch and Tensorflow)

ACL 2022, SimKGC: Simple Contrastive Knowledge Graph Completion with Pre-trained Language Models

[Paper][ACM MM 2024] Making Large Language Models Perform Better in Knowledge Graph Completion

Implementation of TransE model in PyTorch.

ACL 2020: A Re-evaluation of Knowledge Graph Completion Methods

A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization (NAACL 2019)

SimplE Embedding for Link Prediction in Knowledge Graphs

[Neurocomputing 2023] Relational Graph Transformer for Knowledge Graph Representation

End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion

ConMask model described in paper Open-world Knowledge Graph Completion.

AAAI 2020 - InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature Interactions