Pre Trained Language Model

Pre-trained language models (PLMs) are large neural networks trained on massive text datasets, aiming to capture the statistical regularities of language for various downstream tasks. Current research focuses on improving PLM efficiency through techniques like parameter-efficient fine-tuning and exploring their application in diverse fields, including scientific text classification, mental health assessment, and financial forecasting, often leveraging architectures like BERT and its variants. The ability of PLMs to effectively process and generate human language has significant implications for numerous scientific disciplines and practical applications, ranging from improved information retrieval to more sophisticated AI assistants.