Tommaso Caselli

Evaluating the Impact of Source Diversity for RAG in Historical Research

Historical research increasingly benefits from large language models (LLMs). However, LLMs are prone to factual inaccuracy, unreliability, and biased interpretations of data. Retrieval-augmented generation (RAG) approaches have emerged as solutions, but may inadvertently perpetuate biased perspectives embedded in histo...