Papers by Hany Awadalla
Leveraging GPT-4 for Automatic Translation Post-Editing (2023.findings-emnlp)
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| Challenge: | Neural Machine Translation models still require translation post-editing to rectify errors and enhance quality under critical settings. |
| Approach: | They use GPT-4 to automatically post-edit NMT outputs across several language pairs . they show that GPT4 is adept at translation post- editing, producing meaningful edits . |
| Outcome: | The proposed translation post-editor improves on state-of-the-art language models on English-Chinese, English-German, Chinese-English and German-English language pairs. |
Dissecting In-Context Learning of Translations in GPT-3 (2023.findings-emnlp)
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| Challenge: | Recent work on fewshot prompting in Large Language Models has focused on selecting the few-shot samples for prompting. |
| Approach: | They propose a method to add demonstration attributes to prompting in machine translations by perturbations of high-quality in-domain demonstrations. |
| Outcome: | The proposed method improves upon the zero-shot translation performance of GPT-3, even making it competitive with few-shot prompted translations. |