A collection of papers and resources about using KG to help LLMs for inference and QA.
【2023】Unifying Large Language Models and Knowledge Graphs: A Roadmap
【2019】Improving natural language inference using external knowledge in the science questions domain #基于序列模型
【2019】KagNet: Knowledge-aware graph networks for commonsense reasoning #基于序列模型
【2019】ERNIE: Enhanced language representation with informative entities
【2020】Scalable multi-hop relational reasoning for knowledge-aware question answering #基于GNN
【2021】QAGNN: Reasoning with language models and knowledge graphs for question answering #基于GNN
【2022】Greaselm: Graph reasoning enhanced language models
【2023】GrapeQA : GRaph Augmentation and Pruning to Enhance Question-Answering #基于QA-GNN
【2023】KG-GPT: A General Framework for Reasoning on Knowledge Graphs Using Large Language Models
Retrieval-augmented generation for knowledgeintensive nlp tasks
Barack’s wife hillary: Using knowledge graphs for fact-aware language modeling
Realm: Retrieval-augmented language model pre-training
Memory and knowledge augmented language models for inferring salience in long-form stories
An efficient memory-augmented transformer for knowledgeintensive NLP tasks
【2023】Retrieve-Rewrite-Answer: A ==KG==-to-Text Enhanced ==LLM==s Framework for Knowledge Graph Question Answering