@inproceedings{ivchenko-grabar-2026-impact,
    title = "Impact of Text Simplification on Eye-Tracking-Based Reading Profiles Across Domains",
    author = "Ivchenko, Oksana  and
      Grabar, Natalia",
    editor = {Acart{\"u}rk, Cengiz  and
      Can, Burcu  and
      Nasir, Jamal  and
      {\c{C}}{\"o}ltekin, {\c{C}}a{\u{g}}r{\i}},
    booktitle = "Proceedings fo the Second International Workshop on Eye-Tracking Resources and Evaluation for Human-Aligned {NLP}",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELDA",
    url = "https://preview.aclanthology.org/ingest-nlpsi/2026.gaze4nlp-1.4/",
    doi = "10.63317/2qibmhbnsowq",
    pages = "24--29",
    abstract = "Understanding how text readability affects reading behaviour is crucial for improving accessibility and health communication. We analyse sentence-level eye-tracking data from the French Eye-TrAcking (FETA) corpus, which includes original and manually simplified texts from three domains: general, medical, and clinical. Using clustering of fixation-based features, we identify recurrent processing patterns and examine how these patterns change under text simplification. Cluster quality is evaluated using silhouette scores and participant-level bootstrap stability. Simplification does not uniformly reduce reading effort but reorganises processing in domain-dependent ways. Medical texts show strong diversification, general texts moderate diversification, and clinical texts show a reduction in the number of distinct reading profiles. Hence, rather than uniformly facilitating reading, simplification redistributes effort across sentences, underscoring the need for domain-sensitive readability approaches."
}