Retrieval-Augmented Generation for Domain-Specific Assistance: a Legal Case Study
Retrieval-Augmented Generation (RAG) has emerged as an effective paradigm for grounding language-model outputs in verifiable sources while maintaining fluency. However, applying RAG to knowledge-critical domains such as law presents unique challenges: long documents with dense citations, jurisdictional variations, and...