Papers with low resource PCM method

1 papers
Better Quality Estimation for Low Resource Corpus Mining (2022.findings-acl)

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Challenge: State-of-the-art Quality Estimation models lack robustness to out-of domain examples.
Approach: They propose a method that uses multitask training, data augmentation and contrastive learning to achieve better and more robust QE performance.
Outcome: The proposed method improves QE performance significantly in the MLQE challenge and the robustness of QE models when tested in the Parallel Corpus Mining setup.

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