Financial Domain

Research in the financial domain focuses on leveraging large language models (LLMs) to improve various financial tasks, including sentiment analysis, report generation, and question answering. Current efforts concentrate on adapting and fine-tuning LLMs, often using transformer architectures, for specific financial applications, addressing challenges like domain-specific terminology and the need for numerical reasoning. This work aims to enhance efficiency and accuracy in financial analysis, impacting both academic understanding of LLMs and practical applications within the financial industry, such as automated report generation and improved investment decision-making.