Papers with under-translation
Exploiting Pre-Ordering for Neural Machine Translation (L18-1)
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| Challenge: | Existing studies have shown that Neural Machine Translation suffers from the problems that some source words are mistakenly translated for multiple times . |
| Approach: | They propose a pre-ordering approach to solve the under-translation problem by pre-ordnanced source sentences and position embedding to enhance monotone translation. |
| Outcome: | The proposed method significantly improves translation quality by 2.43 BLEU points on Chinese-to-English translation. |
Understanding and Addressing the Under-Translation Problem from the Perspective of Decoding Objective (2024.acl-long)
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| Challenge: | Neural Machine Translation (NMT) has made remarkable progress over the past years, but under-translation and over-translatation remain challenging obstacles faced by NMT systems. |
| Approach: | They propose to employ the confidence of predicting the end of sentence (EOS) as a detector for under-translation and strengthen the confidence-based penalty to penalize candidates with a high risk of under-translated. |
| Outcome: | The proposed method can detect and rectify under-translated outputs, with minor impact on other correct translations. |
Generating Classical Chinese Poems from Vernacular Chinese (D19-1)
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| Challenge: | Existing models for classical Chinese poetry generation only allow users to use keywords to interfere with the meaning of generated poems. |
| Approach: | They propose a model to generate classical Chinese poems from vernacular . their model uses unsupervised machine translation to generate Chinese poems . human evaluation shows it can generate high-quality poems comparable to amateur poems - authors . |
| Outcome: | The proposed model improves the perplexity and BLEU of the proposed model compared with typical models and human evaluation shows it generates high-quality poems comparable to amateur poems. |