Accelerating Materials Language Processing With Large Language Models

This article discusses the integration of GPT models in MLP to improve its effectiveness in materials science research. It also explores the practical applications of GPT-enabled models in tasks such as entity tagging and annotation evaluation. The article presents a general workflow of MLP and compares it to the process of actual materials scientists obtaining information from papers.