Automatic Metrics in Natural Language Generation: A Survey of Current Evaluation Practices
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arXiv
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| Autores principales: | , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
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| _version_ | 1866911993146900480 |
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| author | Schmidtová, Patrícia Mahamood, Saad Balloccu, Simone Dušek, Ondřej Gatt, Albert Gkatzia, Dimitra Howcroft, David M. Plátek, Ondřej Sivaprasad, Adarsa |
| author_facet | Schmidtová, Patrícia Mahamood, Saad Balloccu, Simone Dušek, Ondřej Gatt, Albert Gkatzia, Dimitra Howcroft, David M. Plátek, Ondřej Sivaprasad, Adarsa |
| contents | Automatic metrics are extensively used to evaluate natural language processing systems. However, there has been increasing focus on how they are used and reported by practitioners within the field. In this paper, we have conducted a survey on the use of automatic metrics, focusing particularly on natural language generation (NLG) tasks. We inspect which metrics are used as well as why they are chosen and how their use is reported. Our findings from this survey reveal significant shortcomings, including inappropriate metric usage, lack of implementation details and missing correlations with human judgements. We conclude with recommendations that we believe authors should follow to enable more rigour within the field. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_09169 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Automatic Metrics in Natural Language Generation: A Survey of Current Evaluation Practices Schmidtová, Patrícia Mahamood, Saad Balloccu, Simone Dušek, Ondřej Gatt, Albert Gkatzia, Dimitra Howcroft, David M. Plátek, Ondřej Sivaprasad, Adarsa Computation and Language Automatic metrics are extensively used to evaluate natural language processing systems. However, there has been increasing focus on how they are used and reported by practitioners within the field. In this paper, we have conducted a survey on the use of automatic metrics, focusing particularly on natural language generation (NLG) tasks. We inspect which metrics are used as well as why they are chosen and how their use is reported. Our findings from this survey reveal significant shortcomings, including inappropriate metric usage, lack of implementation details and missing correlations with human judgements. We conclude with recommendations that we believe authors should follow to enable more rigour within the field. |
| title | Automatic Metrics in Natural Language Generation: A Survey of Current Evaluation Practices |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2408.09169 |