General Purpose Language Model

General-purpose language models (GPLMs) are large neural networks trained on massive text datasets to perform a wide range of natural language processing tasks. Current research focuses on improving their efficiency and adaptability, including methods for domain-specific fine-tuning, constraint-based alignment, and techniques to integrate specialized knowledge without sacrificing general capabilities. These advancements are crucial for broadening the applicability of GPLMs across diverse fields, from medicine and materials science to dialogue systems, while addressing challenges like interpretability and resource constraints.