Evaluating the Impact of Source Diversity for RAG in Historical Research
Summary
Historians increasingly use LLMs, and retrieval-augmented generation is often presented as a fix for hallucination. However, archival documents carry the viewpoints of the people who produced them, and RAG may pass those viewpoints on to the model's answers. This study asks whether the country and language of retrieved sources change how models portray a contested historical figure. Napoleon Bonaparte serves as the proof-of-concept case. The authors built a multilingual (English, French, Dutch) collection of newspapers, magazines, books and legal placards from 1805–1819, originating in the UK, US, France and the Netherlands. They filtered it for Napoleon-related material and posed ten historian-designed questions to three Qwen3 models of different sizes, with and without retrieval. Answers were evaluated with BERTScore and ROUGE-L, frame-semantic analysis, and syntactic profiling. Similarity scores stayed high throughout, yet frame analysis revealed clear shifts in perspective. Without retrieval, answers converged on a homogenised view across languages. With RAG, they diversified, and the pattern differed by language. The authors conclude that standard metrics overlook viewpoint effects and that retrieval actively reshapes, rather than neutrally supplements, model perspective.
Key points
- The corpus draws on the British Library, Bibliothèque National de France, KB National Library of the Netherlands, the American Stories dataset, and Dutch-Indonesian placard books.
- The initial collection held over 2.2 million paragraph chunks. BERTopic filtering kept only about 0.41% as Napoleon-relevant.
- English chunks dominate, followed by Dutch and then French. This partly reflects Napoleonic-era censorship decrees in France (1800) and the Netherlands (1810), and the authors deliberately left the data unbalanced.
- The evaluation combines BERTScore/ROUGE-L with frame semantics (partly following Minnema et al., 2022) and syntactic profiling.
- The main finding is that high surface similarity masks substantial, language-specific perspective changes introduced by RAG.
Cite
@inproceedings{mahadeshwar2026evaluating,
title = {{Evaluating the Impact of Source Diversity for RAG in Historical Research}},
author = {Mahadeshwar, Ruhi and Cranenburgh, Andreas van and Caselli, Tommaso and Nissim, Malvina},
booktitle = {Proceedings of the Fifteenth Language Resources and Evaluation Conference},
year = {2026},
doi = {10.63317/4yz9z3uvzasd},
url = {https://doi.org/10.63317/4yz9z3uvzasd}
}References
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