Financial Corpus

Financial corpora are large collections of financial text and data used to train and evaluate large language models (LLMs) for applications in finance. Current research focuses on developing domain-specific LLMs that outperform general-purpose models on tasks like sentiment analysis, question answering, and trading strategy prediction, often employing architectures like BERT, T5, and LLAMA, and incorporating multimodal data such as tables and charts. This work is significant because improved LLMs can enhance financial forecasting, risk management, and regulatory oversight, while also providing valuable benchmarks and datasets for advancing the field of natural language processing in finance.