English

Reproducing the Metric-Based Evaluation of a Set of Controllable Text Generation Techniques

Computation and Language 2024-05-14 v1

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 report of our efforts to rerun a metric-based evaluation of a set of single-attribute and multiple-attribute 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 reporting of the original work.

Keywords

Cite

@article{arxiv.2405.07875,
  title  = {Reproducing the Metric-Based Evaluation of a Set of Controllable Text Generation Techniques},
  author = {Michela Lorandi and Anya Belz},
  journal= {arXiv preprint arXiv:2405.07875},
  year   = {2024}
}

Comments

The Fourth Workshop on Human Evaluation of NLP Systems (HumEval 2024) at LREC-COLING 2024