@article{mahadeshwar-etal-2026-evaluating,
    title = "Evaluating the Impact of Source Diversity for {RAG} in Historical Research",
    author = "Mahadeshwar, Ruhi  and
      van Cranenburgh, Andreas  and
      Caselli, Tommaso  and
      Nissim, Malvina",
    editor = "Piperidis, Stelios  and
      Bel, N{\'u}ria  and
      van den Heuvel, Henk  and
      Ide, Nancy  and
      Krek, Simon  and
      Toral, Antonio",
    journal = "International Conference on Language Resources and Evaluation",
    volume = "main",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resource Association",
    url = "https://preview.aclanthology.org/ingest-lrec/2026.lrec-main.53/",
    pages = "716--734",
    abstract = "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 historical archives. This paper investigates how source diversity in RAG impacts perspective variation in historical question answering. We compile a multilingual corpus (English, French, Dutch) of historical documents spanning multiple countries and focus on Napoleon Bonaparte. We evaluate three Qwen3 models across ten questions using a multi-layered framework combining traditional metrics (BERTScore, ROUGE-L), frame semantics analysis, and syntactic profiling. Our results highlight that, while traditional similarity metrics suggest high semantic consistency, frame-semantic analysis exposes substantial perspective shifts. Baseline answers present ``flattened'' cross-lingual perspectives, whereas RAG introduces diversity. Critically, this diversity manifests differently across languages, demonstrating language-specific patterns. Our findings highlight limitations of traditional evaluation metrics for perspective-sensitive tasks and demonstrate that RAG constitutes active perspective transformation rather than neutral augmentation."
}