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20192026
most citedMachine Learning Explainability for External Stakeholders

41 citations · 165 across the 21 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

Evaluating Intellectual Property Guardrails of Generative Image Models: A Technical Report

Austin T. Hoag, Apostolos Modas, Yunhao Ba +9

Generative image models are capable of producing images that bear a strong resemblance to, or replicate, recognizable intellectual property (IP). In this technical report, we prese…

cs.CV2024

Resampled Datasets Are Not Enough: Mitigating Societal Bias Beyond Single Attributes

Yusuke Hirota, Jerone T. A. Andrews, Dora Zhao +4

We tackle societal bias in image-text datasets by removing spurious correlations between protected groups and image attributes. Traditional methods only target labeled attributes,…

cs.CV20233 cited

Beyond Skin Tone: A Multidimensional Measure of Apparent Skin Color

William Thong, Przemyslaw Joniak, Alice Xiang

This paper strives to measure apparent skin color in computer vision, beyond a unidimensional scale on skin tone. In their seminal paper Gender Shades, Buolamwini and Gebru have sh…

cs.CV20238 cited

Flickr Africa: Examining Geo-Diversity in Large-Scale, Human-Centric Visual Data

Keziah Naggita, Julienne LaChance, Alice Xiang

Biases in large-scale image datasets are known to influence the performance of computer vision models as a function of geographic context. To investigate the limitations of standar…

cs.CV20232 cited

A View From Somewhere: Human-Centric Face Representations

Jerone T. A. Andrews, Przemyslaw Joniak, Alice Xiang

Few datasets contain self-identified sensitive attributes, inferring attributes risks introducing additional biases, and collecting attributes can carry legal risks. Besides, categ…

cs.CV2023

Ethical Considerations for Responsible Data Curation

Jerone T. A. Andrews, Dora Zhao, William Thong +3

Human-centric computer vision (HCCV) data curation practices often neglect privacy and bias concerns, leading to dataset retractions and unfair models. HCCV datasets constructed th…