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Constructing Datasets for Multi-hop Reading Comprehension Across Documents.

, , and . Trans. Assoc. Comput. Linguistics, (2018)

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An empirical analysis of compute-optimal large language model training., , , , , , , , , and 12 other author(s). NeurIPS, (2022)Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehension., , , , and . Trans. Assoc. Comput. Linguistics, (2020)Training datasets for machine reading comprehension and their limitations.. University College London, UK, (2020)British Library, EThOS.Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation., , , , , , , and . EMNLP/IJCNLP (1), page 4081-4091. Association for Computational Linguistics, (2019)Challenges in Detoxifying Language Models., , , , , , , , , and . EMNLP (Findings), page 2447-2469. Association for Computational Linguistics, (2021)Beat the AI: Investigating Adversarial Human Annotations for Reading Comprehension., , , , and . CoRR, (2020)Neural Random Forests., , and . CoRR, (2016)Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Models., , , , , , , , , and 2 other author(s). NeurIPS, (2022)Reducing Sentiment Bias in Language Models via Counterfactual Evaluation., , , , , , , , and . EMNLP (Findings), volume EMNLP 2020 of Findings of ACL, page 65-83. Association for Computational Linguistics, (2020)Crowdsourcing Multiple Choice Science Questions., , and . NUT@EMNLP, page 94-106. Association for Computational Linguistics, (2017)