@inproceedings{vijayachandran-etal-2026-iiith,
    title = "{IIITH} Boys at {S}em{E}val-2026 Task 4: {S}tory{N}et - Understanding Narrative Story Similarity through Symbolic Representations",
    author = "Vijayachandran, Amol  and
      Rajesh, Ananth  and
      Mago, Siddharth  and
      Chitale, Maitreya  and
      Allamraju, Aparajitha",
    editor = "Kochmar, Ekaterina  and
      Ghosh, Debanjan  and
      North, Kai  and
      Komachi, Mamoru",
    booktitle = "Proceedings of the 20th {I}nternational {W}orkshop on {S}emantic {E}valuation (2026)",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.semeval-1.420/",
    pages = "3382--3393",
    ISBN = "979-8-89176-414-9",
    abstract = "Narrative similarity extends beyond standard semantic tasks, requiring alignment of temporal, causal, and emotional structures. We present StoryNet, a framework that represents stories as heterogeneous graphs with character, event, and theme nodes. Stories are decomposed into structured narrative facets using large language models, and similarity is evaluated through both weighted semantic facet comparison and a graph neural network trained with contrastive learning. We analyze how integrating symbolic structure with learned graph representations compares to purely embedding-based baselines."
}