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The Devil is in the Details: Evaluating Limitations of Transformer-based Methods for Granular Tasks.

, , , and . COLING, page 3652-3659. International Committee on Computational Linguistics, (2020)

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Towards a Multimodal Time-Based Empathy Prediction System., , , , , and . FG, page 1-5. IEEE, (2019)Modelling Irony in Twitter: Feature Analysis and Evaluation., and . LREC, page 4258-4264. European Language Resources Association (ELRA), (2014)Do We Criticise (and Laugh) in the Same Way? Automatic Detection of Multi-Lingual Satirical News in Twitter., , and . IJCAI, page 1215-1221. AAAI Press, (2015)Context-Aware Prediction of User Engagement on Online Social Platforms., , , , , and . CoRR, (2023)Sentiment Polarity Classification at EVALITA: Lessons Learned and Open Challenges., , , , , and . IEEE Trans. Affect. Comput., 12 (2): 466-478 (2021)TheRiddlerBot: A next step on the ladder towards creative Twitter bots., , , , and . ICCC, page 315-322. computationalcreativity.net, (2015)On Transferability of Bias Mitigation Effects in Language Model Fine-Tuning., , , , , and . NAACL-HLT, page 3770-3783. Association for Computational Linguistics, (2021)Interpretable Emoji Prediction via Label-Wise Attention LSTMs., , , , and . EMNLP, page 4766-4771. Association for Computational Linguistics, (2018)Shared Task on Stance and Gender Detection in Tweets on Catalan Independence - LaSTUS System Description.. IberEval@SEPLN, volume 1881 of CEUR Workshop Proceedings, page 217-221. CEUR-WS.org, (2017)TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification., , , and . EMNLP (Findings), volume EMNLP 2020 of Findings of ACL, page 1644-1650. Association for Computational Linguistics, (2020)