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SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval).

, , , , , and . SemEval@NAACL-HLT, page 75-86. Association for Computational Linguistics, (2019)

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A Large-Scale Semi-Supervised Dataset for Offensive Language Identification., , , , and . CoRR, (2020)The dark side of news community forums: opinion manipulation trolls., , , , , and . Internet Res., 28 (5): 1292-1312 (2018)Multimodality Representation Learning: A Survey on Evolution, Pretraining and Its Applications., , , , , and . CoRR, (2023)Multimodal Large Language Models to Support Real-World Fact-Checking., , , and . CoRR, (2024)DiscoTK: Using Discourse Structure for Machine Translation Evaluation., , , and . WMT@ACL, page 402-408. The Association for Computer Linguistics, (2014)NUS at WMT09: Domain Adaptation Experiments for English-Spanish Machine Translation of News Commentary Text., and . WMT@EACL, page 75-79. Association for Computational Linguistics, (2009)Category-based Pseudowords., and . HLT-NAACL, The Association for Computational Linguistics, (2003)Batch-Softmax Contrastive Loss for Pairwise Sentence Scoring Tasks., , , and . NAACL-HLT, page 116-126. Association for Computational Linguistics, (2022)Team QCRI-MIT at SemEval-2019 Task 4: Propaganda Analysis Meets Hyperpartisan News Detection., , , , , , and . SemEval@NAACL-HLT, page 1041-1046. Association for Computational Linguistics, (2019)SemEval-2015 Task 10: Sentiment Analysis in Twitter., , , , , and . SemEval@NAACL-HLT, page 451-463. The Association for Computer Linguistics, (2015)