Financial LANGuage Model

Financial Language Models (FLMs) are large language models specifically trained on financial data to improve the analysis and understanding of financial text and information. Current research focuses on developing more robust FLMs by incorporating diverse financial corpora into training, employing novel training objectives like masked language modeling tailored to financial terminology, and establishing comprehensive benchmark datasets for evaluating model performance across various NLP tasks. These advancements aim to overcome limitations of existing models, such as biases and poor generalization, leading to more accurate and reliable tools for financial professionals and researchers.