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RiTUAL-UH at SemEval-2017 Task 5: Sentiment Analysis on Financial Data Using Neural Networks.

, , and . SemEval@ACL, page 877-882. Association for Computational Linguistics, (2017)

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Preventing Catastrophic Forgetting in Continual Learning of New Natural Language Tasks., , , , and . KDD, page 3137-3145. ACM, (2022)LinCE: A Centralized Benchmark for Linguistic Code-switching Evaluation., , and . LREC, page 1803-1813. European Language Resources Association, (2020)SentNoB: A Dataset for Analysing Sentiment on Noisy Bangla Texts., , , and . EMNLP (Findings), page 3265-3271. Association for Computational Linguistics, (2021)MultiCoNER v2: a Large Multilingual dataset for Fine-grained and Noisy Named Entity Recognition., , , , and . EMNLP (Findings), page 2027-2051. Association for Computational Linguistics, (2023)Multi-view Story Characterization from Movie Plot Synopses and Reviews., , , and . EMNLP (1), page 5629-5646. Association for Computational Linguistics, (2020)Integrating Summarization and Retrieval for Enhanced Personalization via Large Language Models., , , , , , , and . CoRR, (2023)Attending the Emotions to Detect Online Abusive Language., , , , and . WOAH, page 79-88. Association for Computational Linguistics, (2020)Folksonomication: Predicting Tags for Movies from Plot Synopses using Emotion Flow Encoded Neural Network., , and . COLING, page 2879-2891. Association for Computational Linguistics, (2018)Age Suitability Rating: Predicting the MPAA Rating Based on Movie Dialogues., , , and . LREC, page 1327-1335. European Language Resources Association, (2020)SemEval-2023 Task 2: Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2)., , , , and . SemEval@ACL, page 2247-2265. Association for Computational Linguistics, (2023)