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Elo Uncovered: Robustness and Best Practices in Language Model Evaluation., , , , and . CoRR, (2023)Learning Topic-Sensitive Word Representations., , and . ACL (2), page 441-447. Association for Computational Linguistics, (2017)Back-Translation Sampling by Targeting Difficult Words in Neural Machine Translation., and . EMNLP, page 436-446. Association for Computational Linguistics, (2018)InPars: Unsupervised Dataset Generation for Information Retrieval., , , and . SIGIR, page 2387-2392. ACM, (2022)InPars-v2: Large Language Models as Efficient Dataset Generators for Information Retrieval., , , , , , and . CoRR, (2023)Data Augmentation for Low-Resource Neural Machine Translation., , and . ACL (2), page 567-573. Association for Computational Linguistics, (2017)The Unreasonable Volatility of Neural Machine Translation Models., and . NGT@ACL, page 88-96. Association for Computational Linguistics, (2020)Examining the Tip of the Iceberg: A Data Set for Idiom Translation., , and . LREC, European Language Resources Association (ELRA), (2018)Which Prompts Make The Difference? Data Prioritization For Efficient Human LLM Evaluation., , , , and . CoRR, (2023)A New Neural Search and Insights Platform for Navigating and Organizing AI Research., , , , , and . SDP@EMNLP, page 207-213. Association for Computational Linguistics, (2020)