Papers by Ramakrishna Appicharla
Reference Free Domain Adaptation for Translation of Noisy Questions with Question Specific Rewards (2023.findings-emnlp)
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Baban Gain, Ramakrishna Appicharla, Soumya Chennabasavaraj, Nikesh Garera, Asif Ekbal, Muthusamy Chelliah
| Challenge: | Creating a synthetic parallel corpus from noisy data is also difficult due to its noisy nature. |
| Approach: | They propose a training methodology that fine-tunes the NMT system only using source-side data to balance adequacy and fluency. |
| Outcome: | The proposed method surpasses the MLE-based fine-tuning approach by achieving a 1.9 BLEU improvement. |