Oral Argument

Oral argument, a crucial component of legal proceedings, is increasingly becoming a focus of computational analysis to understand its influence on judicial decision-making. Current research utilizes machine learning techniques to analyze the content of oral arguments, particularly the questions posed by judges, to build predictive models of judicial outcomes and uncover subtle aspects of judicial reasoning and questioning styles. This work leverages large language models and novel approaches like simulated cross-examination to assess the factuality of claims made during arguments, improving the reliability of automated legal analysis and potentially enhancing the overall fairness and transparency of legal processes.