Lin, Akin, Rao, Hie, et al. Language models of protein sequences at the scale of evolution enable accurate structure prediction. Science 2023. Code Morgan HL (1965) The generation of a unique machine description for chemical struct...
Knowledge Graph Exploring the Intersection of Neo4j and Large Language Models 3 min read Developer GenAI Machine Learning Harnessing Large Language Models With Neo4j 4 min read See More Build Smarter Apps Faster Learn how to work with connected data using a graph database with no JOINs. ...
众所周知,大语言模型(Large Language Models,LLMs)是通过自回归式的 Causal Language Modeling 实现预训练,自然语言文本遵循着 token-by-token的序列形式实现文本生成和推理。然而,图(Graph)则不是序列模式的数据,因此,如何让一个以序列为感知的大语言模型很好地理解一个图数据,是一大挑战。
在 LlamaIndex 和 LangChain 中,NebulaGraph 引入了一系列知识图谱和图存储工具,支持编排、图谱与大模型间的交互。之前,NebulaGraph 布道师古思为作为这项工作的主要贡献者已向大家详细介绍了如何构建图谱、Text2Cypher、GraphRAG、GraphIndex 等方法,并展示了相关示例与效果。
Learn how Graph Query Language (GQL) has just been approved to become an international standards project and why we need a standard graph query language.
Large Language Models Find meaningful results using large language models (LLMs), no matter how complex your data or where it is stored. Graph Query Engine Get answers in a flash with the fastest graph query engine on the market - no code required. ...
This project aims to build the world's largest graph of language models. To our knowledge, it is the first attempt to construct such a graph. Have a look at our design demo. In this graph, we will integrate many different specialized models and train the respective Octopus models for the...
Can language models solve graph problems in natural language?, 2023a. ^Jiayan Guo, Lun Du, and Hengyu Liu. Gpt4graph: Can large language models understand graph structured data ? an empirical evaluation and benchmarking. ArXiv, abs/2305.15066, 2023....
1. Introduction1.1 Background GNNs的一大优势是其捕捉graph中潜在结构信息和依赖的能力,得益于message passing和aggregation机制,GNNs可以有效传播和结合信息; 近些年来多种GNN架构出现:GCNs、GATs和GTNs等…
提炼并记录文章中的五个优秀句式,并尝试在未来的写作中模仿使用。 “This raises the question: “Can we generalize heterogeneous graph models to be well-adapted to diverse downstream learning tasks with distribution shifts in both node token sets and relation type heterogeneity?””(Tang 等, 2024, p....