2024
COLING
COLING 2024
Reproducing the Metric-Based Evaluation of a Set of Controllable Text Generation Techniques
Abstract
AbstractRerunning 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.
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Cross-Pollinator
— Artificial Intelligence, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Natural Language Processing, Reinforcement Learning