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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 1 of 1 1 The UMD Submission to the Explainable MT Quality Estimation Shared Task: Combining Explanation Models with Sequence Labeling ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Carpuat, Marine; Kabir, Tasnim. - : Underline Science Inc., 2021 Abstract: This presentation describes the UMD submission to the Explainable Quality Estimation Shared Task at the Eval4NLP 2021 Workshop on ``Evaluation & Comparison of NLP Systems''. We participated in the word-level and sentence-level MT Quality Estimation (QE) constrained tasks for all language pairs: Estonian-English, Romanian-English, German-Chinese, and Russian-German. Our approach combines the predictions of a word-level explainer model on top of a sentence-level QE model and a sequence labeler trained on synthetic data. These models are based on pre-trained multilingual language models and do not require any word-level annotations for training, making them well suited to zero-shot settings. Our best performing system improves over the best baseline across all metrics and language pairs, with an average gain of 0.1 in AUC, Average Precision, and Recall at Top-K score. ... Keyword: Machine Learning; Material Culture; Natural Language Processing URL: https://underline.io/lecture/39301-the-umd-submission-to-the-explainable-mt-quality-estimation-shared-task-combining-explanation-models-with-sequence-labeling https://dx.doi.org/10.48448/hxe1-f287 BASE Hide details

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