@inproceedings{mondella-etal-2024-reprohum,
    title = "{R}epro{H}um {\#}0892-01: The painful route to consistent results: A reproduction study of human evaluation in {NLG}",
    author = "Mondella, Irene  and
      Lai, Huiyuan  and
      Nissim, Malvina",
    editor = "Balloccu, Simone  and
      Belz, Anya  and
      Huidrom, Rudali  and
      Reiter, Ehud  and
      Sedoc, Joao  and
      Thomson, Craig",
    booktitle = "Proceedings of the Fourth Workshop on Human Evaluation of NLP Systems (HumEval) @ LREC-COLING 2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2024.humeval-1.24/",
    pages = "261--268",
    abstract = "In spite of the core role human judgement plays in evaluating the performance of NLP systems, the way human assessments are elicited in NLP experiments, and to some extent the nature of human judgement itself, pose challenges to the reliability and validity of human evaluation. In the context of the larger ReproHum project, aimed at running large scale multi-lab reproductions of human judgement, we replicated the understandability assessment by humans on several generated outputs of simplified text described in the paper {\textquotedblleft}Neural Text Simplification of Clinical Letters with a Domain Specific Phrase Table{\textquotedblright} by Shardlow and Nawaz, appeared in the Proceedings of ACL 2019. Although we had to implement a series of modifications compared to the original study, which were necessary to run our human evaluation on exactly the same data, we managed to collect assessments and compare results with the original study. We obtained results consistent with those of the reference study, confirming their findings. The paper is complete with as much information as possible to foster and facilitate future reproduction."
}