Papers by Hoa Nguyen
BMX: Boosting Natural Language Generation Metrics with Explainability (2024.findings-eacl)
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| Challenge: | Modern language model (LM) based natural language generation evaluation metrics achieve astonishing results in grading machine generated sentences like humans would. |
| Approach: | They use word-level explanations to convert a word- level score into a segment-level score and combine this segment- level with the original metric to obtain a better metric. |
| Outcome: | The proposed metrics improve across MT and summarization datasets while achieving small improvements on machine translation. |