Papers by Graeme Blackwood
Synthetic Pre-Training Tasks for Neural Machine Translation (2023.findings-acl)
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| Challenge: | toxicity and bias can be addressed by pre-training with synthetic resources . BLEU scores are used to compare methods with real-world data . |
| Approach: | They propose several ways to generate obfuscated data from large parallel corpus and concatenating phrase pairs from small word-aligned corpus with synthetic parallel data without real human language corpora. |
| Outcome: | The proposed methods can be used to generate obfuscated data or synthetic parallel data without real human language corpora even with high levels of oblication. |
Multilingual Neural Machine Translation with Task-Specific Attention (C18-1)
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| Challenge: | Multilingual machine translation is a task of building a system capable of translating between multiple source and target languages. |
| Approach: | They propose task-specific attention models to retain parameter sharing generalization . they observe improved translation quality even in low-resource zero-shot directions . |
| Outcome: | The proposed model retains parameter sharing generalization while allowing language-specific specialization . it improves translation quality even in low-resource zero-shot translation directions . |