Papers with Translation-based methods
Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction (N18-1)
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| Challenge: | Existing grammar correction methods are limited in their ability to correct highly local errors . evaluators are unable to distinguish noisy examples from nonsynthesized ones . |
| Approach: | They propose to synthesize parallel data by noising a clean monolingual corpus . they propose to apply noise to the corpus to syntherize additional noisy examples . |
| Outcome: | The proposed method can produce almost as strong results as training with nonsynthesized data. |
Cross-Lingual Knowledge Transfer for Clinical Phenotyping (2022.lrec-1)
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Jens-Michalis Papaioannou, Paul Grundmann, Betty van Aken, Athanasios Samaras, Ilias Kyparissidis, George Giannakoulas, Felix Gers, Alexander Loeser
| Challenge: | Current models for clinical phenotyping are limited to clinical notes written in English due to the large amount of labeled and unlabeled clinical text resources. |
| Approach: | They propose to use translation-based methods with domain-specific encoders and cross-lingual encoder plus adapters to perform this task for clinics that do not use the English language. |
| Outcome: | The proposed strategies outperform the state-of-the-art models for clinics that do not use the English language and have a small amount of in-domain data available. |