100 citations · 177 across the 6 of their papers we have counts for
11 papers
Better Together? An Evaluation of AI-Supported Code Translation
Justin D. Weisz, Michael Muller, Steven I. Ross +5
Generative machine learning models have recently been applied to source code, for use cases including translating code between programming languages, creating documentation from co…
Investigating Explainability of Generative AI for Code through Scenario-based Design
Jiao Sun, Q. Vera Liao, Michael Muller +4
What does it mean for a generative AI model to be explainable? The emergent discipline of explainable AI (XAI) has made great strides in helping people understand discriminative mo…
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…
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…
Quality Estimation & Interpretability for Code Translation
Mayank Agarwal, Kartik Talamadupula, Stephanie Houde +5
Recently, the automated translation of source code from one programming language to another by using automatic approaches inspired by Neural Machine Translation (NMT) methods for n…
Towards evaluating and eliciting high-quality documentation for intelligent systems
David Piorkowski, Daniel González, John Richards +1
A vital component of trust and transparency in intelligent systems built on machine learning and artificial intelligence is the development of clear, understandable documentation.…