most citedA Preliminary Framework for Intersectionality in ML Pipelines

4 citations · 8 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SE2025

Explaining Code Risk in OSS: Towards LLM-Generated Fault Prediction Interpretations

Elijah Kayode Adejumo, Brittany Johnson

Open Source Software (OSS) has become a very important and crucial infrastructure worldwide because of the value it provides. OSS typically depends on contributions from developers…

cs.SE2025

An Empirical Validation of Open Source Repository Stability Metrics

Elijah Kayode Adejumo, Brittany Johnson

Over the past few decades, open source software has been continuously integrated into software supply chains worldwide, drastically increasing reliance and dependence. Because of t…

cs.SE2025

What Makes a Fairness Tool Project Sustainable in Open Source?

Sadia Afrin Mim, Fatemeh Vares, Andrew Meenly +1

As society becomes increasingly reliant on artificial intelligence, the need to mitigate risk and harm is paramount. In response, researchers and practitioners have developed tools…

cs.LG20254 cited

A Preliminary Framework for Intersectionality in ML Pipelines

Michelle Nashla Turcios, Alicia E. Boyd, Angela D. R. Smith +1

Machine learning (ML) has become a go-to solution for improving how we use, experience, and interact with technology (and the world around us). Unfortunately, studies have repeated…

cs.LG20251 cited

Causality-Driven Neural Network Repair: Challenges and Opportunities

Fatemeh Vares, Brittany Johnson

Deep Neural Networks (DNNs) often rely on statistical correlations rather than causal reasoning, limiting their robustness and interpretability. While testing methods can identify…

cs.HC20253 cited

Exploring Culturally Informed AI Assistants: A Comparative Study of ChatBlackGPT and ChatGPT

Lisa Egede, Ebtesam Al Haque, Gabriella Thompson +3

In recent years, we have seen an influx in reliance on AI assistants for information seeking. Given this widespread use and the known challenges AI poses for Black users, recent ef…