@inproceedings{lorandi-belz-2024-reproducing,
    title = "Reproducing the Metric-Based Evaluation of a Set of Controllable Text Generation Techniques",
    author = "Lorandi, Michela  and
      Belz, Anya",
    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://aclanthology.org/2024.humeval-1.12",
    pages = "125--131",
    abstract = "Rerunning a metric-based evaluation should be more straightforward and results should be closer than in a human-based evaluation, especially where code and model checkpoints are made available by the original authors. As this brief report of our efforts to rerun a metric-based evaluation of a set of multi-aspect controllable text generation (CTG) techniques shows however, such reruns of evaluations do not always produce results that are the same as the original results, and can reveal errors in the orginal work.",
}

Rerunning a metric-based evaluation should be more straightforward and results should be closer than in a human-based evaluation, especially where code and model checkpoints are made available by the original authors. As this brief report of our efforts to rerun a metric-based evaluation of a set of multi-aspect controllable text generation (CTG) techniques shows however, such reruns of evaluations do not always produce results that are the same as the original results, and can reveal errors in the orginal work.
Lor i, Michela Belz, Anya
Reproducing the Metric-Based Evaluation of a Set of Controllable Text Generation Techniques