Legal Article

Research on applying large language models (LLMs) to legal tasks focuses on improving access to justice and enhancing legal professionals' efficiency. Current efforts center on developing LLMs for tasks like legal intake, advice generation, and thematic analysis within case law, often employing techniques like instruction tuning, mixture-of-experts models, and contrastive learning to improve accuracy and interpretability. These advancements aim to address challenges such as the "hallucination" problem in LLMs and the need for explainable AI in the legal domain, ultimately impacting legal research and potentially streamlining legal processes.