@article{tewari-etal-2026-musia,
    title = "{MUSIA}: Multilingual Story Illustration Corpus for Cross-Cultural Alignment and Generation",
    author = "Tewari, Krishna  and
      Chanda, Supriya  and
      Patil, Nirmit  and
      Pal, Sukomal",
    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.150/",
    pages = "1914--1924",
    abstract = "Recent advances in text-to-image generation have enabled automated visual storytelling, yet most existing datasets remain monolingual and culturally narrow. We introduce MUSIA, a Multilingual Story Illustration Corpus designed to advance research in cross-lingual and culturally grounded narrative illustration. MUSIA comprises bilingual (English-Hindi) story-image pairs drawn from open literary and folk sources, curated to reflect diverse cultural themes, artistic styles, and linguistic structures. Each story includes multiple illustrations aligned at the scene level, accompanied by quality-verified mappings for narrative-visual coherence. To establish a reproducible benchmark, we propose a two-stage baseline combining transformer-based semantic summarization with diffusion-based image generation, achieving strong performance in relevance, visual quality, and consistency. MUSIA represents the first step toward a scalable, culturally inclusive benchmark for multilingual visual storytelling, enabling fair and reproducible research across low-resource and underrepresented languages."
}