Papers by Jeewon Ha
Shuffled-token Detection for Refining Pre-trained RoBERTa (2021.naacl-srw)
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| Challenge: | State-of-the-art transformer models have achieved robust performance on a variety of NLP tasks. |
| Approach: | They propose to refine a pre-trained NLP model by detecting shuffled tokens . they use a sequential approach to train a model using random shuffling . |
| Outcome: | The proposed model achieves better performance on 4 out of 7 GLUE tasks. |