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"Diversity and Uncertainty in Moderation" are the Key to Data Selection for Multilingual Few-shot Transfer.

, , and . NAACL-HLT (Findings), page 1042-1055. Association for Computational Linguistics, (2022)

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Too Brittle To Touch: Comparing the Stability of Quantization and Distillation Towards Developing Lightweight Low-Resource MT Models., , , , and . CoRR, (2022)On the Economics of Multilingual Few-shot Learning: Modeling the Cost-Performance Trade-offs of Machine Translated and Manual Data., , and . NAACL-HLT, page 1369-1384. Association for Computational Linguistics, (2022)DiTTO: A Feature Representation Imitation Approach for Improving Cross-Lingual Transfer., , , , and . EACL, page 385-406. Association for Computational Linguistics, (2023)On the Universality of Deep Contextual Language Models., , , , and . ICON, page 106-119. NLP Association of India (NLPAI), (2021)Wisdom of Students: A Consistent Automatic Short Answer Grading Technique., , , and . ICON, page 178-187. NLP Association of India, (2016)MATREX: The DCU MT System for WMT 2010., , , , , , , , , and . WMT@ACL, page 143-148. Association for Computational Linguistics, (2010)A Fluctuation Smoothing Approach for Unsupervised Automatic Short Answer Grading., , and . NLP-TEA@COLING, page 82-91. The COLING 2016 Organizing Committee, (2016)Identifying Transferable Information Across Domains for Cross-domain Sentiment Classification., , , and . ACL (1), page 968-978. Association for Computational Linguistics, (2018)Translating Web Search Queries into Natural Language Questions., , and . LREC, European Language Resources Association (ELRA), (2018)Translating Web Search Queries into Natural Language Questions., , and . CoRR, (2020)