A curated list of resources dedicated to retrieval-augmented generation (RAG).

Some papers on knowledge graph embedding

开源社区第一个能下载、能运行的中文 LLaMA2 模型！

https://kg-beyond-triple.github.io/

The implementation of Relational Rule Enhanced Graph Neural Network (RUN-GNN)

[IJCAI 2024] FactCHD: Benchmarking Fact-Conflicting Hallucination Detection

CLEVER 2023: Continual Learning for Generative Retrieval over Dynamic Corpora

[Paper List] Papers integrating knowledge graphs (KGs) and large language models (LLMs)

A pipeline using LLMs for Knowledge Engineering, combining knowledge probing and Wikidata entity mapping.

Knowledge Graph Reasoning with Relational Digraph. WebConf 2022

Exploring large language models for knowledge graph completion

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

[CIKM2023] HyperFormer: Enhancing Entity and Relation Interaction for Hyper-Relational Knowledge Graph Completion

Pytorch implementation of StreamE

IntelliGraphs is a collection of graph datasets for benchmarking generative models for knowledge graphs.

Released codes of the RETIA model.

CAT-Walk is an inducive method that learns hyperedge representations via a novel higher-order random walk, SetWalk.

Official implementation of Inductive Logical Query Answering in Knowledge Graphs (NeurIPS 2022)

Lifelong Embedding Learning and Transfer for Growing Knowledge Graphs, AAAI 2023

Inductive relation prediction by subgraph reasoning, ICML'20

Inductive Knowledge Graph Reasoning for Multi-batch Emerging Entities, CIKM 2022

Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)

InGram: Inductive Knowledge Graph Embedding via Relation Graphs (ICML 2023)