From questions to insights: a reproducible question-answering pipeline for historiographical corpus exploration

This short presentation focuses on a reproducible Information Retrieval Q&A pipeline using RAG framework tailored for historiographical corpora, specifically the theses abstracts of our university (3,000+ texts in French). It addresses retrieval challenges by integrating vector-based indexing, semantic search, and LLMs, offering structured, contextualized responses to enhance research and exploration in large corpora.