LLMs tend to lose prior skills when fine-tuned for new tasks. A new self-distillation approach aims to reduce regression and ...

It’s a common enough scenario in many synthesis labs: you know what starting material you have, and you know what product you need but not quite what reaction conditions will get you there. Unless you ...

The team used an AI method known as equation discovery to develop a model to simulate the interactions between small eddies—circular, vortex-like currents—and large-scale ones. These interactions are ...

Abstract: This paper investigates a GraphRAG framework that integrates knowledge graphs into the Retrieval-Augmented Generation (RAG) architecture to enhance networking applications. While RAG has ...

Background: Biomedical knowledge graphs (KGs), such as the Data Distillery Knowledge Graph (DDKG), capture known relationships among entities (e.g., genes, diseases, proteins), providing valuable ...

AI hallucinations about a brand come in many types: A generative AI system might show a person who isn’t the actual founder, display the wrong address for the headquarters, or describe an old product ...

Credit: Image generated by VentureBeat with FLUX-pro-1.1 Without data, enterprise AI isn't going to be successful. Getting all the data in one place and having the right type of data tools, including ...

A TechRadar article noted that nearly 90% of enterprise information (documents, emails, videos) lies dormant in unstructured systems. This "dark data" isn't just neglected; it's a liability. GenAI ...

According to DeepLearning.AI, it launched a short course titled Agentic Knowledge Graph Construction in collaboration with Neo4j and taught by Andreas Kollegger to show how knowledge graphs complement ...

In this tutorial, we’ll show how to create a Knowledge Graph from an unstructured document using an LLM. While traditional NLP methods have been used for extracting entities and relationships, Large ...