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Bridging the domain gap in cross-lingual document classification., , , and . CoRR, (2019)Toward Opinion Summarization: Linking the Sources, and . Proceedings of the Workshop on Sentiment and Subjectivity in Text, page 9--14. Sydney, Australia, Association for Computational Linguistics, (July 2006)Topic Identification for Fine-Grained Opinion Analysis., and . COLING, page 817-824. (2008)Self-training Improves Pre-training for Natural Language Understanding., , , , , , , and . NAACL-HLT, page 5408-5418. Association for Computational Linguistics, (2021)Improving In-Context Few-Shot Learning via Self-Supervised Training., , , , , , and . NAACL-HLT, page 3558-3573. Association for Computational Linguistics, (2022)Minimum-Risk Training of Approximate CRF-Based NLP Systems., and . HLT-NAACL, page 120-130. The Association for Computational Linguistics, (2012)SemEval-2013 Task 2: Sentiment Analysis in Twitter., , , , , and . SemEval@NAACL-HLT, page 312-320. The Association for Computer Linguistics, (2013)SemEval-2016 Task 4: Sentiment Analysis in Twitter., , , , and . SemEval@NAACL-HLT, page 1-18. The Association for Computer Linguistics, (2016)SemEval-2014 Task 9: Sentiment Analysis in Twitter, , , , and . (Aug 1, 2014)Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure., , and . AISTATS, volume 15 of JMLR Proceedings, page 725-733. JMLR.org, (2011)