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CODA-19: Reliably Annotating Research Aspects on 10,000+ CORD-19 Abstracts Using a Non-Expert Crowd.

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Challenges in Providing Automatic Affective Feedback in Instant Messaging Applications., , and . AAAI Spring Symposia, AAAI Press, (2017)Location Prediction for Tweets., , , and . Frontiers Big Data, (2019)If in a Crowdsourced Data Annotation Pipeline, a GPT-4., , , , and . CoRR, (2024)GPT-4 as an Effective Zero-Shot Evaluator for Scientific Figure Captions., , , , , and . EMNLP (Findings), page 5464-5474. Association for Computational Linguistics, (2023)Towards a Better Learning of Near-Synonyms: Automatically Suggesting Example Sentences via Fill in the Blank., , and . WWW (Companion Volume), page 293-302. ACM, (2017)What Types of Questions Require Conversation to Answer? A Case Study of AskReddit Questions., , , and . CHI Extended Abstracts, page 319:1-319:9. ACM, (2023)MoodSwipe: A Soft Keyboard that Suggests MessageBased on User-Specified Emotions., , , , , , and . EMNLP (System Demonstrations), page 73-78. Association for Computational Linguistics, (2017)Assessing the Helpfulness of Learning Materials with Inference-Based Learner-Like Agent., , , , and . EMNLP (1), page 3807-3817. Association for Computational Linguistics, (2020)From Receptive to Productive: Learning to Use Confusing Words through Automatically Selected Example Sentences., , , and . BEA@ACL, page 461-471. Association for Computational Linguistics, (2019)GiveMeExample: Learning confusing words by example sentences., and . ASONAM, page 1414-1417. IEEE Computer Society, (2016)