Papers by Evgeny Matusov
Learning from Chunk-based Feedback in Neural Machine Translation (P18-2)
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| Challenge: | a common problem with explicit ratings of translations is that users are not qualified enough to provide reliable feedback for the whole sentence. |
| Approach: | They propose a way to learn from partial feedback in neural machine translation . they ask users to highlight a correct chunk of a translation based on partial feedback . |
| Outcome: | The proposed method outperforms sentence-based feedback by 2.61% BLEU absolute. |
Can Neural Machine Translation be Improved with User Feedback? (N18-3)
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| Challenge: | a recent study has focused on the use of explicit and implicit feedback for neural machine translation (NMT) a new study uses explicit and implied feedback to improve performance of NMT with human reinforcement. |
| Approach: | They propose to use real logged feedback to improve neural machine translation with human reinforcement. |
| Outcome: | The proposed method improves translation quality metrics with implicit task-based feedback . the proposed method is based on explicit and implicit feedback collected on the eBay platform . |