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OCHADAI-KYODAI at SemEval-2021 Task 1: Enhancing Model Generalization and Robustness for Lexical Complexity Prediction.

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OCHADAI-KYOTO at SemEval-2021 Task 1: Enhancing Model Generalization and Robustness for Lexical Complexity Prediction., , , and . SemEval@ACL/IJCNLP, page 17-23. Association for Computational Linguistics, (2021)Attention-Focused Adversarial Training for Robust Temporal Reasoning.. LREC, page 7352-7359. European Language Resources Association, (2022)AcTED: Automatic Acquisition of Typical Event Duration for Semi-supervised Temporal Commonsense QA., , , , , and . CoRR, (2024)Toward Building a Language Model for Understanding Temporal Commonsense., , and . AACL/IJCNLP 2022 (Student Research Workshop), page 17-24. Association for Computational Linguistics, (2022)OCHADAI-KYODAI at SemEval-2021 Task 1: Enhancing Model Generalization and Robustness for Lexical Complexity Prediction., , , and . CoRR, (2021)Effective Masked Language Modeling for Temporal Commonsense Reasoning., , and . SCIS/ISIS, page 1-4. IEEE, (2022)Multi-Layer Random Perturbation Training for improving Model Generalization Efficiently., , and . BlackboxNLP@EMNLP, page 303-310. Association for Computational Linguistics, (2021)Dependency Enhanced Contextual Representations for Japanese Temporal Relation Classification., , , , and . PACLIC, page 170-179. Association for Computational Lingustics, (2021)