@inproceedings{tran-etal-2026-unh,
    title = "{UNH} @ {R}ag4{R}eports: A Broad Exploration of {LLM}-Judges for {RAG}",
    author = "Tran, Minna  and
      McCarthy, Ryan  and
      Parsons, Aiden  and
      Unzen, Jaren  and
      Dietz, Laura",
    editor = "Yang, Eugene  and
      Lawrie, Dawn  and
      MacAvaney, Sean  and
      Mayfield, James  and
      Soldaini, Luca  and
      Yates, Andrew",
    booktitle = "Proceedings of the 1st Workshop on Multilingual Report Generation via Retrieval Augmented Generation ({RAG}4{R}eports 2026)",
    month = jul,
    year = "2026",
    address = "San Diego, CA, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.rag4reports-1.9/",
    pages = "71--76",
    ISBN = "979-8-89176-417-0",
    abstract = "We submitted a breadth of LLM-as-a-Judge approaches to Rag4Reports Task A; our top method ranked first among all submitted systems. We find that citation faithfulness is the most essential signal, and that content is best verified by checking whether cited documents cover nuggets generated from the LLM{'}s internal knowledge."
}