arXiv:2006.14799cs.CL
Evaluation of Text Generation: A Survey
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Abstract
The paper surveys evaluation methods of natural language generation (NLG) systems that have been developed in the last few years. We group NLG evaluation methods into three categories: (1) human-centric evaluation metrics, (2) automatic metrics that require no training, and (3) machine-learned metrics. For each category, we discuss the progress that has been made and the challenges still being faced, with a focus on the evaluation of recently proposed NLG tasks and neural NLG models. We then present two examples for task-specific NLG evaluations for automatic text summarization and long text generation, and conclude the paper by proposing future research directions.
Forer effect material was written by humans, one might note... But there was a paper just the other day on more rigorous evaluation: https://arxiv.org/abs/2006.14799
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