497 citations · 2k across the 21 of their papers we have counts for
8 papers · 1 filter
Using Document Similarity Methods to create Parallel Datasets for Code Translation
Mayank Agarwal, Kartik Talamadupula, Fernando Martinez +5
Translating source code from one programming language to another is a critical, time-consuming task in modernizing legacy applications and codebases. Recent work in this space has…
The Who in XAI: How AI Background Shapes Perceptions of AI Explanations
Upol Ehsan, Samir Passi, Q. Vera Liao +4
Explainability of AI systems is critical for users to take informed actions. Understanding "who" opens the black-box of AI is just as important as opening it. We conduct a mixed-me…
Increasing the Speed and Accuracy of Data LabelingThrough an AI Assisted Interface
Michael Desmond, Zahra Ashktorab, Michelle Brachman +8
Labeling data is an important step in the supervised machine learning lifecycle. It is a laborious human activity comprised of repeated decision making: the human labeler decides w…
Perfection Not Required? Human-AI Partnerships in Code Translation
Justin D. Weisz, Michael Muller, Stephanie Houde +5
Generative models have become adept at producing artifacts such as images, videos, and prose at human-like levels of proficiency. New generative techniques, such as unsupervised ne…
Documentation Matters: Human-Centered AI System to Assist Data Science Code Documentation in Computational Notebooks
April Yi Wang, Dakuo Wang, Jaimie Drozdal +6
Computational notebooks allow data scientists to express their ideas through a combination of code and documentation. However, data scientists often pay attention only to the code,…
How AI Developers Overcome Communication Challenges in a Multidisciplinary Team: A Case Study
David Piorkowski, Soya Park, April Yi Wang +3
The development of AI applications is a multidisciplinary effort, involving multiple roles collaborating with the AI developers, an umbrella term we use to include data scientists…
Expanding Explainability: Towards Social Transparency in AI systems
Upol Ehsan, Q. Vera Liao, Michael Muller +2
As AI-powered systems increasingly mediate consequential decision-making, their explainability is critical for end-users to take informed and accountable actions. Explanations in h…
How Much Automation Does a Data Scientist Want?
Dakuo Wang, Q. Vera Liao, Yunfeng Zhang +5
Data science and machine learning (DS/ML) are at the heart of the recent advancements of many Artificial Intelligence (AI) applications. There is an active research thread in AI, \…