MTRACE: Multilingual Retrieval-Augmented Generation for Temporally Diverse Text Corpora
A multilingual Retrieval-Augmented Generation pipeline was created to answer questions about noisy, historical documents spanning different time periods. It uses hybrid search techniques and structured generation prompts to ensure answers are grounded in evidence and correctly state when information is missing, making it robust for historical text QA.