Visual Cues and Error Correction for Translation Robustness (2021.findings-emnlp)
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| Challenge: | Existing robustness techniques fail when faced with unseen types of noise and their performance degrades on clean texts. |
| Approach: | They propose visual context to improve translation robustness for noisy texts . they also propose an error correction training regime that can be used as an auxiliary task . |
| Outcome: | The proposed training regime improves translation robustness on noisy texts while maintaining translation quality on clean texts. |
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