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Improving Adverse Drug Event Extraction with SpanBERT on Different Text Typologies., , , , , and . CoRR, (2021)BomJi at SemEval-2018 Task 10: Combining Vector-, Pattern- and Graph-based Information to Identify Discriminative Attributes., , and . SemEval@NAACL-HLT, page 990-994. Association for Computational Linguistics, (2018)LLT-PolyU: Identifying Sentiment Intensity in Ironic Tweets., , , and . SemEval@NAACL-HLT, page 673-678. The Association for Computer Linguistics, (2015)SemEval-2018 Task 9: Hypernym Discovery., , , , , , , , and . SemEval@NAACL-HLT, page 712-724. Association for Computational Linguistics, (2018)Negation Detection for Robust Adverse Drug Event Extraction From Social Media Texts., , , , and . IRCDL, volume 3160 of CEUR Workshop Proceedings, CEUR-WS.org, (2022)Did the Cat Drink the Coffee? Challenging Transformers with Generalized Event Knowledge., , , , , and . *SEM, page 1-11. Association for Computational Linguistics, (2021)Taking Antonymy Mask off in Vector Space., , , and . PACLIC, page 135-144. The PACLIC 28 Organizing Committee and PACLIC Steering Committee / ACL / Department of Linguistics, Faculty of Arts, Chulalongkorn University, (2014)Increasing Adverse Drug Events extraction robustness on social media: case study on negation and speculation., , , , and . CoRR, (2022)Decoding Word Embeddings with Brain-Based Semantic Features., , , and . Comput. Linguistics, 47 (3): 663-698 (2021)Unsupervised Measure of Word Similarity: How to Outperform Co-Occurrence and Vector Cosine in VSMs., , , , and . AAAI, page 4260-4261. AAAI Press, (2016)