Papers with deterministic segmentations

1 papers
Deterministic Reversible Data Augmentation for Neural Machine Translation (2024.findings-acl)

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Challenge: Recent neural machine translation models have improved translation quality but they also introduce small perturbations like misspelling and paraphrasing.
Approach: They propose a method that generates multi-granularity subword representations with reversible operations and deterministic segmentations.
Outcome: The proposed method outperforms strong baselines on several translation tasks with a clear margin and exhibits good robustness in noisy, low-resource, and cross-domain datasets.

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