@inproceedings{lowphansirikul-ittichaiwong-2026-otter,
    title = "Otter at {M}ed{E}x{A}ct2026: Diverse Encoder Ensemble for Medical Decision Span Detection",
    author = "Lowphansirikul, Lalita  and
      Ittichaiwong, Piyalitt",
    editor = "Gupta, Deepak  and
      Demner-Fushman, Dina",
    booktitle = "Proceedings of the {B}io{NLP} 2026 (Shared Tasks)",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.bionlp-2.7/",
    pages = "47--53",
    ISBN = "979-8-89176-435-4",
    abstract = "We build an ensemble of 10 transformer encoders for the MedExACT 2026 shared task on medical decision span detection. The ensemble is diversified along three training directions: encoder initialization (including domain-adaptive pre-training on clinical text), loss function, and data augmentation with LLM-generated synthetic notes and silver-labeled clinical documents. Greedy forward search selects the combination with the highest validation final score. A BERT-based boundary refiner is applied to the ensemble{'}s predicted spans to correct offset errors before submission."
}