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“Who doesn't like dinosaurs?” Finding and Eliciting Richer Preferences for Recommendation, , and . Fourteenth ACM Conference on Recommender Systems, page 398-407. ACM, (September 2020)The Label Complexity of Mixed-Initiative Classifier Training., , and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 2800-2809. JMLR.org, (2016)Toward Responsible AI by Planning to Fail.. KDD, page 3607. ACM, (2020)Sketching NLP: A Case Study of Exploring the Right Things To Design with Language Intelligence., , , , and . CHI, page 185. ACM, (2019)Guidelines for Human-AI Interaction, , , , , , , , , and 3 other author(s). Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI \textquotesingle19, page 1-13. ACM Press, (2019)Unsupervised and supervised machine learning in user modeling for intelligent learning environments., and . IUI, page 72-81. ACM, (2007)Examining multiple potential models in end-user interactive concept learning., , , and . CHI, page 1357-1360. ACM, (2010)Amplifying community content creation with mixed initiative information extraction., , , , , and . CHI, page 1849-1858. ACM, (2009)A Dataset and Evaluation Metrics for Abstractive Compression of Sentences and Short Paragraphs., , , and . EMNLP, page 340-350. The Association for Computational Linguistics, (2016)Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions., , and . ACL (1), page 575-593. Association for Computational Linguistics, (2023)