Browsing by Author "Mensa, Enrico"

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    Large Language Models for Museum Label Optimization: A Case Study on Ministerial Compliance and Cultural Accessibility in Galleria Sabauda's Flemish Collection
    (The Eurographics Association, 2025) Macaluso, Melissa; Mensa, Enrico; Marras, Anna Maria; Pisano, Paola; Campana, Stefano; Ferdani, Daniele; Graf, Holger; Guidi, Gabriele; Hegarty, Zackary; Pescarin, Sofia; Remondino, Fabio
    This paper examines how Large Language Models (LLMs) can be applied to optimize art museum labels to meet specific cultural accessibility needs and ministerial guidelines and best practices in matters of exhibit texts redaction. The paper illustrates the first results of an experiment on optimizing the current labels of the Flemish section of the Galleria Sabauda in Turin. The study tests three state-of-art-LLMs, GPT4.o mini, Claude 3.7 and DeepSeek V-3, according to three different few-shot prompting techniques. An evaluation grid is created to assess the performance of LLMs in this rewriting task considering both content optimization and readability and formatting aspects.
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    ''There was a scribe, a priest and a thief''. Testing the potential of language models for the creation of curatorial narratives in an archaeological museum
    (The Eurographics Association, 2025) Mensa, Enrico; Fulfaro, Chiara; Fubini, Flavia; Bottino, Andrea; Antonino, Riccardo; Ferraris, Enrico; Damiano, Rossana; Campana, Stefano; Ferdani, Daniele; Graf, Holger; Guidi, Gabriele; Hegarty, Zackary; Pescarin, Sofia; Remondino, Fabio
    In the cultural heritage sector, Artificial Intelligence can aid in the creation of narratives by enhancing human creativity and assisting cultural heritage professionals in crafting and developing stories. In this work we focus specifically on how large language models can support rather than replace curatorial expertise. While AI can generate content, crafting compelling narratives requires human understanding of narrative structures, cultural context, and thematic coherence. We present a platform that helps curators create interactive stories for museums through AI assistance, developed as part of the CHANGES project at the Egyptian Museum in Turin. The platform enables curatorial narrative creation with selective LLM support, connects stories to museum collections via semantic annotation, and facilitates translation to venue-specific technical formats. Rather than having LLMs generate complete stories, curators construct the narrative framework while using LLMs to transform structured scene descriptions into polished prose. Our evaluation with three state-of-the-art models across 147 scenes and in a real use-case scenario shows that current LLMs can effectively complete this constrained creative task, though all outputs still require human refinement. This curator-driven approach ensures that generated narratives maintain the accuracy and scholarly standards essential for cultural heritage contexts while benefiting from AI's linguistic capabilities.