@inproceedings{wong-2026-fu,
    title = "{FU}-{HU}-P5 at {\#}{SMM}4{H}-{H}ea{RD} 2026: {M}ed{S}ynth Dialogue-to-Note Generation",
    author = "Wong, Jessica Ying En",
    editor = "Lopez-Garcia, Guillermo  and
      Gonzalez-Hernandez, Graciela",
    booktitle = "Proceedings of the 11th Social Media Mining for Health Research and Applications ({SMM}4{H}-{H}ea{RD} 2026) Workshop and Shared Tasks",
    month = jul,
    year = "2026",
    address = "San Diego, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.smm4h-1.38/",
    pages = "237--239",
    ISBN = "979-8-89176-432-3",
    abstract = "This paper demonstrates our system for shared task 4 of {\#}SMM4H-HeaRD 2026 Workshop where a given doctor-patient dialogue is summarized into a clinical note in the corresponding SOAP format. Our proposed solution includes semi-supervised learning together with parameter efficient finetuning (PEFT) applied to a lightweight pre-trained QWEN3.5 model. Our model delivers competitive performance relative to its parameter count, and generalizes its performance to unseen test dataset."
}