@inproceedings{lee-etal-2025-heart,
    title = "From Heart to Words: Generating Empathetic Responses via Integrated Figurative Language and Semantic Context Signals",
    author = "Lee, Gyeongeun  and
      Wang, Zhu  and
      Ravi, Sathya N.  and
      Parde, Natalie",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/display_plenaries/2025.findings-acl.231/",
    pages = "4490--4502",
    ISBN = "979-8-89176-256-5",
    abstract = "Although generically expressing empathy is straightforward, effectively conveying empathy in specialized settings presents nuanced challenges. We present a conceptually motivated investigation into the use of figurative language and causal semantic context to facilitate targeted empathetic response generation within a specific mental health support domain, studying how these factors may be leveraged to promote improved response quality. Our approach achieves a 7.6{\%} improvement in BLEU, a 36.7{\%} reduction in Perplexity, and a 7.6{\%} increase in lexical diversity (D-1 and D-2) compared to models without these signals, and human assessments show a 24.2{\%} increase in empathy ratings. These findings provide deeper insights into grounded empathy understanding and response generation, offering a foundation for future research in this area."
}