activity
20192023
most citedJury Learning: Integrating Dissenting Voices into Machine Learning Models

130 citations · 291 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2023★ 10 cited

Cura: Curation at Social Media Scale

Wanrong He, Mitchell L. Gordon, Lindsay Popowski +1

How can online communities execute a focused vision for their space? Curation offers one approach, where community leaders manually select content to share with the community. Cura…

cs.HC2022★ 130 cited

Jury Learning: Integrating Dissenting Voices into Machine Learning Models

Mitchell L. Gordon, Michelle S. Lam, Joon Sung Park +4

Whose labels should a machine learning (ML) algorithm learn to emulate? For ML tasks ranging from online comment toxicity to misinformation detection to medical diagnosis, differen…

cs.CV2019★ 4 cited

Approximating Human Judgment of Generated Image Quality

Y. Alex Kolchinski, Sharon Zhou, Shengjia Zhao +2

Generative models have made immense progress in recent years, particularly in their ability to generate high quality images. However, that quality has been difficult to evaluate ri…

cs.CY2019★ 49 cited

Goal-setting And Achievement In Activity Tracking Apps: A Case Study Of MyFitnessPal

Mitchell L. Gordon, Tim Althoff, Jure Leskovec

Activity tracking apps often make use of goals as one of their core motivational tools. There are two critical components to this tool: setting a goal, and subsequently achieving t…

cs.CV2019★ 98 cited

HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models

Sharon Zhou, Mitchell L. Gordon, Ranjay Krishna +3

Generative models often use human evaluations to measure the perceived quality of their outputs. Automated metrics are noisy indirect proxies, because they rely on heuristics or pr…