Papers with PBD
Pretrained Bidirectional Distillation for Machine Translation (2023.acl-long)
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| Challenge: | Existing studies have focused on language knowledge transfer from pretrained models to neural machine translation models. |
| Approach: | They propose to use masked language pretraining to efficiently transfer bidirectional language knowledge to NMT models. |
| Outcome: | The proposed method can significantly improve machine translation performance and achieve competitive or even better results than previous methods. |
Pseudo-Bidirectional Decoding for Local Sequence Transduction (2020.findings-emnlp)
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| Challenge: | Local sequence transduction tasks involve massive overlapping between source and target sequences . experimental results show that Pseudo-Bidirectional Decoding improves performance of standard seq2seq models. |
| Approach: | They propose a simple but versatile approach for local sequence transduction tasks . they propose to copy source tokens to decoder as pseudo future context . |
| Outcome: | The proposed approach improves the performance of standard seq2seq models on LST tasks. |