Legal Document

Legal document processing is a rapidly evolving field focused on improving the efficiency and accuracy of tasks involving legal texts, primarily through the application of natural language processing (NLP) techniques. Current research emphasizes developing and refining large language models (LLMs) and other deep learning architectures, such as BERT and transformer-based models, for tasks like legal text summarization, case retrieval, and judgment prediction, often incorporating techniques like curriculum learning and multi-task learning to enhance performance. This work is significant because it promises to automate time-consuming legal tasks, improve access to justice, and facilitate more efficient and informed legal decision-making.