Papers with COMET-KIWI
Improving NMT Models by Retrofitting Quality Estimators into Trainable Energy Loss (2025.coling-main)
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| Challenge: | Reinforcement learning has shown great promise in aligning language models with human preferences in a variety of text generation tasks, including machine translation. |
| Approach: | They propose a method that employs quality estimators as trainable loss networks to backpropagate to the NMT model. |
| Outcome: | The proposed method outperforms strong baselines and proximal policy optimizations on English-to-Mongolian translation. |