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RuSentiment: An Enriched Sentiment Analysis Dataset for Social Media in Russian.

, , , , , and . COLING, page 755-763. Association for Computational Linguistics, (2018)

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Getting Closer to AI Complete Question Answering: A Set of Prerequisite Real Tasks., , , and . AAAI, page 8722-8731. AAAI Press, (2020)RuSentiment: An Enriched Sentiment Analysis Dataset for Social Media in Russian., , , , , and . COLING, page 755-763. Association for Computational Linguistics, (2018)The (too Many) Problems of Analogical Reasoning with Word Vectors., , and . *SEM, page 135-148. Association for Computational Linguistics, (2017)'Just What do You Think You're Doing, Dave?' A Checklist for Responsible Data Use in NLP., , and . EMNLP (Findings), page 4821-4833. Association for Computational Linguistics, (2021)The ROOTS Search Tool: Data Transparency for LLMs., , , , , , , and . CoRR, (2023)Adversarial Decomposition of Text Representation., , , and . NAACL-HLT (1), page 815-825. Association for Computational Linguistics, (2019)Outlier Dimensions that Disrupt Transformers are Driven by Frequency., , , and . EMNLP (Findings), page 1286-1304. Association for Computational Linguistics, (2022)Investigating Different Syntactic Context Types and Context Representations for Learning Word Embeddings., , , , , , and . EMNLP, page 2421-2431. Association for Computational Linguistics, (2017)Revealing the Dark Secrets of BERT., , , and . EMNLP/IJCNLP (1), page 4364-4373. Association for Computational Linguistics, (2019)On the Interaction of Belief Bias and Explanations., , and . ACL/IJCNLP (Findings), volume ACL/IJCNLP 2021 of Findings of ACL, page 2930-2942. Association for Computational Linguistics, (2021)