Papers by Amy Pu
Learning Compact Metrics for MT (2021.emnlp-main)
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| Challenge: | Recent advances in machine translation and multilingual text generation have led researchers to adopt trained metrics such as COMET or BLEURT, which treat evaluation as a regression problem and use representations from multilingual pre-trained models such as XLM-RoBERTa or mBERT. |
| Approach: | They propose to use multilingual model capacity to improve model performance by transferring knowledge from one teacher to multiple students trained on related languages. |
| Outcome: | The proposed model yields 10.5% improvement over vanilla fine-tuning and reaches 92.6% of RemBERT’s performance using only a third of its parameters. |