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+ Pre-trained evaluator in EMNLP 2022 paper
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+ *[Towards a Unified Multi-Dimensional Evaluator for Text Generation](https://arxiv.org/abs/2210.07197)*
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+ ## Introduction
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+ **Multi-dimensional evaluation** is the dominant paradigm for human evaluation in Natural Language Generation (NLG), i.e., evaluating the generated text from multiple explainable dimensions, such as coherence and fluency.
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+ However, automatic evaluation in NLG is still dominated by similarity-based metrics (e.g., ROUGE, BLEU), but they are not sufficient to portray the difference between the advanced generation models.
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+ Therefore, we propose **UniEval** to bridge this gap so that a more comprehensive and fine-grained evaluation of NLG systems can be achieved.
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+ ## Pre-trained Evaluator
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+ **unieval-dialog** is the pre-trained evaluator for the dialogue response generation task. It can evaluate the model output from five dimensions:
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+ - *naturalness*
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+ - *coherence*
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+ - *engagingness*
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+ - *groundedness*
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+ - *understandability*
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+ ## Usage
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+ Please refer to [our GitHub repository](https://github.com/maszhongming/UniEval).