@inproceedings{zeweniuk-etal-2025-beyond,
    title = "Beyond Paraphrasing: Analyzing Summarization Abstractiveness and Reasoning",
    author = "Zeweniuk, Nathan  and
      Ernst, Ori  and
      Cheung, Jackie CK",
    editor = "Dong, Yue  and
      Xiao, Wen  and
      Zhang, Haopeng  and
      Zhang, Rui  and
      Ernst, Ori  and
      Wang, Lu  and
      Liu, Fei",
    booktitle = "Proceedings of The 5th New Frontiers in Summarization Workshop",
    month = nov,
    year = "2025",
    address = "Hybrid",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2025.newsum-main.4/",
    pages = "48--58",
    ISBN = "979-8-89176-337-1",
    abstract = "While there have been many studies analyzing the ability of LLMs to solve problems through reasoning, their application of reasoning in summarization remains largely unexamined. This study explores whether reasoning is essential to summarization by investigating three questions: (1) Do humans frequently use reasoning to generate new summary content? (2) Do summarization models exhibit the same reasoning patterns as humans? (3) Should summarization models integrate more complex reasoning abilities? Our findings reveal that while human summaries often contain reasoning-based information, system-generated summaries rarely contain this same information. This suggests that models struggle to effectively apply reasoning, even when it could improve summary quality. We advocate for the development of models that incorporate deeper reasoning and abstractiveness, and we release our annotated data to support future research."
}