22 citations · 39 across the 13 of their papers we have counts for
15 papers
MLGuard: Defend Your Machine Learning Model!
Sheng Wong, Scott Barnett, Jessica Rivera-Villicana +4
Machine Learning (ML) is used in critical highly regulated and high-stakes fields such as finance, medicine, and transportation. The correctness of these ML applications is importa…
Garbage in, garbage out: Zero-shot detection of crime using Large Language Models
Anj Simmons, Rajesh Vasa
This paper proposes exploiting the common sense knowledge learned by large language models to perform zero-shot reasoning about crimes given textual descriptions of surveillance vi…
Comparative analysis of real bugs in open-source Machine Learning projects -- A Registered Report
Tuan Dung Lai, Anj Simmons, Scott Barnett +2
Background: Machine Learning (ML) systems rely on data to make predictions, the systems have many added components compared to traditional software systems such as the data process…
Signal Knowledge Graph
Anj Simmons, Rajesh Vasa
This paper presents an knowledge graph to assist in reasoning over signals for intelligence purposes. We highlight limitations of existing knowledge graphs and reasoning systems fo…
Requirements of API Documentation: A Case Study into Computer Vision Services
Alex Cummaudo, Rajesh Vasa, John Grundy +1
Using cloud-based computer vision services is gaining traction, where developers access AI-powered components through familiar RESTful APIs, not needing to orchestrate large traini…
Threshy: Supporting Safe Usage of Intelligent Web Services
Alex Cummaudo, Scott Barnett, Rajesh Vasa +1
Increased popularity of `intelligent' web services provides end-users with machine-learnt functionality at little effort to developers. However, these services require a decision t…