Case Retrieval

Case retrieval focuses on efficiently identifying legally similar cases, aiding legal professionals and improving judicial efficiency. Current research emphasizes improving retrieval accuracy by incorporating diverse legal factors beyond simple textual similarity, utilizing techniques like multi-task learning, contrastive learning, and various embedding methods (e.g., BERT, TF-IDF) within retrieval-augmented generation (RAG) frameworks. These advancements aim to enhance the precision and interpretability of case matching, ultimately impacting legal decision-making and promoting fairer, more consistent judicial outcomes.