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Deep contextualized word representations for detecting sarcasm and irony.

, , , and . WASSA@EMNLP, page 2-7. Association for Computational Linguistics, (2018)

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Gating Mechanisms for Combining Character and Word-level Word Representations: an Empirical Study., and . NAACL-HLT (Student Research Workshop), page 110-124. Association for Computational Linguistics, (2019)IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word Representations., , and . WASSA@EMNLP, page 50-56. Association for Computational Linguistics, (2018)Refining Raw Sentence Representations for Textual Entailment Recognition via Attention., , , and . RepEval@EMNLP, page 51-55. Association for Computational Linguistics, (2017)A Multi-modal Approach to Fine-grained Opinion Mining on Video Reviews., , , , and . CoRR, (2020)IIIDYT at SemEval-2018 Task 3: Irony detection in English tweets., , , , and . SemEval@NAACL-HLT, page 537-540. Association for Computational Linguistics, (2018)Combining eye tracking, pupil dilation and EEG analysis for predicting web users click intention., , and . Inf. Fusion, (2017)Mining fine-grained opinions on closed captions of YouTube videos with an attention-RNN., , and . WASSA@EMNLP, page 102-111. Association for Computational Linguistics, (2017)Opinion Mining and Information Fusion: A survey., and . Inf. Fusion, (2016)Deep contextualized word representations for detecting sarcasm and irony., , , and . WASSA@EMNLP, page 2-7. Association for Computational Linguistics, (2018)Learning to Describe Editing Activities in Collaborative Environments: A Case Study on GitHub and Wikipedia., , , and . PACLIC, page 188-198. Association for Computational Linguistics, (2020)