Development and Validation of ML-DQA - a Machine Learning Data Quality Assurance Framework for Healthcare. - Mark P. Sendak; Gaurav Sirdeshmukh; Timothy Ochoa; Hayley Premo; Linda Tang; Kira Niederhoffer; Sarah Reed; Kaivalya Deshpande; Emily Sterrett; Melissa Bauer; Laurie Snyder; Afreen Shariff; et al. (MLHC, 2022)

Exploring Why Object Recognition Performance Degrades Across Income Levels and Geographies with Factor Annotations. - Laura Gustafson; Megan Richards; Melissa Hall; Caner Hazirbas; Diane Bouchacourt; Mark Ibrahim (NeurIPS, 2023)

Pinpointing Why Object Recognition Performance Degrades Across Income Levels and Geographies. - Laura Gustafson; Megan Richards; Melissa Hall; Caner Hazirbas; Diane Bouchacourt; Mark Ibrahim (CoRR, 2023)

Does Progress On Object Recognition Benchmarks Improve Real-World Generalization? - Megan Richards; Polina Kirichenko; Diane Bouchacourt; Mark Ibrahim (CoRR, 2023)

Does Progress On Object Recognition Benchmarks Improve Generalization on Crowdsourced, Global Data? - Megan Richards; Polina Kirichenko; Diane Bouchacourt; Mark Ibrahim (ICLR, 2024)

An Introduction to Vision-Language Modeling. - Florian Bordes; Richard Yuanzhe Pang; Anurag Ajay; Alexander C. Li; Adrien Bardes; Suzanne Petryk; Oscar Mañas; Zhiqiu Lin; Anas Mahmoud 002; Bargav Jayaraman; Mark Ibrahim; Melissa Hall; et al. (CoRR, 2024)

Decomposed evaluations of geographic disparities in text-to-image models. - Abhishek Sureddy; Dishant Padalia; Nandhinee Periyakaruppa; Oindrila Saha; Adina Williams; Adriana Romero-Soriano; Megan Richards; Polina Kirichenko; Melissa Hall (CoRR, 2024)

On the Role of Speech Data in Reducing Toxicity Detection Bias. - Samuel J. Bell; Mariano Coria Meglioli; Megan Richards; Eduardo Sánchez; Christophe Ropers; Skyler Wang; Adina Williams; Levent Sagun; Marta R. Costa-jussà (NAACL (Long Papers), 2025)