Papers with strong semi-supervised approaches
Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference (2021.eacl-main)
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| Challenge: | Existing approaches to learning from examples are limited due to the vast number of languages, domains and tasks. |
| Approach: | They propose a semi-supervised training procedure that reformulates input examples as cloze-style phrases to help language models understand a given task. |
| Outcome: | The proposed approach outperforms supervised training and strong semi-supervised approaches in low-resource settings by a large margin. |