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      BUT-FIT at SemEval-2020 Task 5: Automatic detection of counterfactual statements with deep pre-trained language representation models

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          Abstract

          This paper describes BUT-FIT's submission at SemEval-2020 Task 5: Modelling Causal Reasoning in Language: Detecting Counterfactuals. The challenge focused on detecting whether a given statement contains a counterfactual (Subtask 1) and extracting both antecedent and consequent parts of the counterfactual from the text (Subtask 2). We experimented with various state-of-the-art language representation models (LRMs). We found RoBERTa LRM to perform the best in both subtasks. We achieved the first place in both exact match and F1 for Subtask 2 and ranked second for Subtask 1.

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          Author and article information

          Journal
          28 July 2020
          Article
          2007.14128

          http://creativecommons.org/publicdomain/zero/1.0/

          Custom metadata
          cs.CL cs.LG stat.ML

          Theoretical computer science, Machine learning, Artificial intelligence

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