Legal Reasoning

Legal reasoning research focuses on developing computational models that can understand and emulate human legal reasoning, aiming to improve efficiency and fairness in legal processes. Current research heavily utilizes large language models (LLMs), often enhanced with retrieval-augmented generation (RAG) or fine-tuned on specialized legal datasets, to perform tasks like legal judgment prediction, question answering, and argumentation analysis. These advancements are significant because they offer the potential to automate time-consuming legal tasks, improve access to justice, and provide more transparent and consistent legal decision-making.