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The Label Complexity of Mixed-Initiative Classifier Training., , and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 2800-2809. JMLR.org, (2016)“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)Sketching NLP: A Case Study of Exploring the Right Things To Design with Language Intelligence., , , , and . CHI, page 185. ACM, (2019)Supporting Human-AI Collaboration in Auditing LLMs with LLMs., , , and . CoRR, (2023)Aligning Offline Metrics and Human Judgments of Value of AI-Pair Programmers., , , , , and . CoRR, (2022)Toward Responsible AI by Planning to Fail.. KDD, page 3607. ACM, (2020)Unsupervised and supervised machine learning in user modeling for intelligent learning environments., and . IUI, page 72-81. ACM, (2007)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)Machine Teaching: A New Paradigm for Building Machine Learning Systems., , , , , , , , , and 1 other author(s). CoRR, (2017)AHA!: Facilitating AI Impact Assessment by Generating Examples of Harms., , , , , and . CoRR, (2023)