NeuroSymbolic AI for Legal AI-TRISM: Trustworthy, Reliable, Interpretable, Safe Models

The article introduces the TRISM framework, which integrates NeuroSymbolic AI principles with Large Language Models (LLMs) to enhance their reliability and interpretability in legal applications. It addresses the limitations of current LLMs, such as inadequate structured legal knowledge integration and lack of verification mechanisms, by employing Retrieval-Augmented Generation (RAG) and formalizing symbolic legal knowledge extraction. This framework is significant for practitioners as it aims to improve the accuracy of legal text analysis and generation, ensuring safer and more interpretable outputs in legal contexts.