Judgment Prediction

Legal judgment prediction aims to automatically forecast court decisions based on case details, assisting legal professionals and improving judicial efficiency. Current research heavily utilizes large language models (LLMs) and hierarchical neural frameworks, often incorporating techniques like multi-task learning and causal inference to enhance prediction accuracy and robustness, particularly addressing challenges posed by lengthy and unstructured legal documents. This field is significant for its potential to automate legal analysis, improve access to justice, and uncover biases within legal systems, though challenges remain in ensuring fairness and generalizability across diverse legal contexts and languages.