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When is multitask learning effective? Semantic sequence prediction under varying data conditions, and . (2016)cite arxiv:1612.02251Comment: In EACL 2017.Subdomain Sensitive Statistical Parsing using Raw Corpora., and . LREC, European Language Resources Association, (2008)When POS data sets don't add up: Combatting sample bias., , and . LREC, page 4472-4475. European Language Resources Association (ELRA), (2014)Mining for unambiguous instances to adapt part-of-speech taggers to new domains., , , and . HLT-NAACL, page 1256-1261. The Association for Computational Linguistics, (2015)NLP North at WNUT-2020 Task 2: Pre-training versus Ensembling for Detection of Informative COVID-19 English Tweets., , and . W-NUT@EMNLP, page 331-336. Association for Computational Linguistics, (2020)Exploring the Robustness of Task-oriented Dialogue Systems for Colloquial German Varieties., , and . EACL (1), page 445-468. Association for Computational Linguistics, (2024)Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLP., , , , and . EACL (System Demonstrations), page 176-197. Association for Computational Linguistics, (2021)When is multitask learning effective? Semantic sequence prediction under varying data conditions., and . EACL (1), page 44-53. Association for Computational Linguistics, (2017)Using Frame Semantics for Knowledge Extraction from Twitter., , and . AAAI, page 2447-2452. AAAI Press, (2015)Exploring an Auxiliary Distribution Based Approach to Domain Adaptation of a Syntactic Disambiguation Model., and . CF+CDPE@COLING, page 9-16. Coling 2008 Organizing Committee, (2008)