Papers with language-agnostic method

2 papers
A Simple Recipe for Multilingual Grammatical Error Correction (2021.acl-short)

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Challenge: Modern approaches view the task of Grammatical Error Correction (GEC) as monolingual text-to-text rewriting and employ encoderdecoder neural architectures.
Approach: They propose a language-agnostic method to generate a large number of synthetic examples and use large-scale multilingual language models to train state-of-the-art GEC models.
Outcome: The proposed method surpasses state-of-the-art results on GEC benchmarks in English, Czech, German and Russian.
PR-MCS: Perturbation Robust Metric for MultiLingual Image Captioning (2023.findings-emnlp)

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Challenge: Existing image captioning metrics are vulnerable to lexical perturbations, but they are not robust to such perturbations.
Approach: They propose a perturbation-robust multilingual CLIPScore which is a reference-free image captioning metric for multiple languages.
Outcome: The proposed metric outperforms baseline metrics in capturing lexical noise of all various perturbation types in all five languages while maintaining a strong correlation with human judgments.

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