G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment (2023.emnlp-main)
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| Challenge: | Conventional reference-based metrics have low correlation with human judgments, especially for open-ended generation tasks. |
| Approach: | They propose to use large language models as reference-free NLG evaluators to assess the quality of NLG outputs. |
| Outcome: | The proposed framework outperforms all previous methods in two generation tasks, and has a Spearman correlation of 0.514 with human on summarization task, and a large variance in human judgments. |
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