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Bibliographic Details
Main Authors: Lorandi, Michela, Belz, Anya
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2405.07875
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author Lorandi, Michela
Belz, Anya
author_facet Lorandi, Michela
Belz, Anya
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2405_07875
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Reproducing the Metric-Based Evaluation of a Set of Controllable Text Generation Techniques
Lorandi, Michela
Belz, Anya
Computation and Language
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.
title Reproducing the Metric-Based Evaluation of a Set of Controllable Text Generation Techniques
topic Computation and Language
url https://arxiv.org/abs/2405.07875