If you are interested in learning how to build knowledge graphs using artificial intelligence and specifically large language models (LLM). Johannes Jolkkonen has created a fantastic tutorial that ...

A team of researchers at ETH Zurich are working on a novel approach to solving increasingly large graph problems. Large graphs are a basis of many problems in social sciences (e.g., studying human ...

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...

In recent years, knowledge graphs have become an important tool for organizing and accessing large volumes of enterprise data in diverse industries — from healthcare to industrial, to banking and ...

Triangle counting stands as a fundamental task in graph theory and network science, offering critical insights into the structural properties of complex systems. By enumerating all sets of three ...

Graph Neural Networks (GNNs) have gained widespread adoption in recommendation systems. When it comes to processing large graphs, GNNs may encounter the scalability issue stemming from their ...

Graph databases such as Neo4j, TigerGraph, Amazon Neptune, the graph portion of Azure Cosmos DB, and AnzoGraph, the subject of this review, offer a natural representation of data that is primarily ...

It has been an exhilarating year in combinatorics research. In early 2023, mathematicians were stunned when two of the biggest problems in the field were solved in as many months. Now, a third major ...

LLMs are advanced AI systems that have the ability to understand and generate human-like text. They work by predicting what word comes next in a sentence, learning from vast amounts of data. Knowledge ...