The evaluation of Natural Language Generation (NLG) models has gained increased attention, urging the development of metrics that evaluate various aspects of generated text. LUNA addresses this challenge by introducing a unified interface for 20 NLG evaluation metrics. These metrics are categorized based on their reference-dependence and the type of text representation they employ, from string-based n-gram overlap to the utilization of static embeddings and pre-trained language models. The straightforward design of LUNA allows for easy extension with novel metrics, requiring just a few lines of code. LUNA offers a user-friendly tool for evaluating generated texts.
LUNA: A Framework for Language Understanding and Naturalness Assessment
LUNA provides a unified interface for evaluating Natural Language Generation models using a diverse set of 20 metrics across reference-dependence and text representation types.
- Year
- 2024
- Venue
- arXiv 2024
- Authors
- 5
- Hosting
- Abstract onlyARXIV-DEFAULT
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- Abstract & full text
- arxiv.org/abs/2401.04522ARXIV-DEFAULT
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