Papers by Akifumi Nakamachi
Text Simplification with Reinforcement Learning Using Supervised Rewards on Grammaticality, Meaning Preservation, and Simplicity (2020.aacl-srw)
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| Challenge: | Existing studies in text-to-text generation do not align with human-perspectives for these perspectives. |
| Approach: | They propose to use BERT regressors fine-tuned for grammaticality, meaning preservation, and simplicity as reward estimators to optimize rewards for text simplification. |
| Outcome: | The proposed method achieves text simplification conforming to human-perspectives. |