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The Disagreement Deconvolution: Bringing Machine Learning Performance Metrics In Line With Reality.

, , , , and . CHI, page 388:1-388:14. ACM, (2021)

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Approximating Human Judgment of Generated Image Quality., , , , and . CoRR, (2019)End-User Audits: A System Empowering Communities to Lead Large-Scale Investigations of Harmful Algorithmic Behavior., , , , , and . Proc. ACM Hum. Comput. Interact., 6 (CSCW2): 1-34 (2022)Cura: Curation at Social Media Scale., , , and . CoRR, (2023)Jury Learning: Integrating Dissenting Voices into Machine Learning Models., , , , , , and . CHI, page 115:1-115:19. ACM, (2022)HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models., , , , , and . NeurIPS, page 3444-3456. (2019)Glance Privacy: Obfuscating Personal Identity While Coding Behavioral Video., , , , , and . HCOMP, page 18-19. AAAI, (2014)CrowdMask: Using Crowds to Preserve Privacy in Crowd-Powered Systems via Progressive Filtering., , , , , , and . HCOMP, page 89-97. AAAI Press, (2017)Glance: rapidly coding behavioral video with the crowd., , , , , and . UIST, page 551-562. ACM, (2014)Codepourri: Creating visual coding tutorials using a volunteer crowd of learners., and . VL/HCC, page 13-21. IEEE Computer Society, (2015)Touchscreen Haptic Augmentation Effects on Tapping, Drag and Drop, and Path Following., and . CHI, page 373. ACM, (2019)