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Prompt Discriminative Language Models for Domain Adaptation.

, , , , , , , , and . ClinicalNLP@ACL, page 247-258. Association for Computational Linguistics, (2023)

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Length, Interchangeability, and External Knowledge: Observations from Predicting Argument Convincingness., , and . IJCNLP(1), page 342-351. Asian Federation of Natural Language Processing, (2017)Tracking Bias in News Sources Using Social Media: the Russia-Ukraine Maidan Crisis of 2013-2014., , , and . NLPmJ@EMNLP, page 13-18. Association for Computational Linguistics, (2017)SemEval-2017 Task 6: #HashtagWars: Learning a Sense of Humor., , and . SemEval@ACL, page 49-57. Association for Computational Linguistics, (2017)Towards Debate Automation: a Recurrent Model for Predicting Debate Winners., and . EMNLP, page 2465-2475. Association for Computational Linguistics, (2017)Prompt Discriminative Language Models for Domain Adaptation., , , , , , , , and . ClinicalNLP@ACL, page 247-258. Association for Computational Linguistics, (2023)Operationalizing the Legal Principle of Data Minimization for Personalization., , , , and . SIGIR, page 399-408. ACM, (2020)Here's My Point: Joint Pointer Architecture for Argument Mining., , and . EMNLP, page 1364-1373. Association for Computational Linguistics, (2017)Combining Network and Language Indicators for Tracking Conflict Intensity., , , , , , and . SocInfo (2), volume 10540 of Lecture Notes in Computer Science, page 391-404. Springer, (2017)Playing log(N)-Questions over Sentences., and . CoRR, (2019)Ranking Passages for Argument Convincingness., , and . ArgMining@ACL, page 146-155. Association for Computational Linguistics, (2019)