11 citations · 19 across the 7 of their papers we have counts for
7 papers
A Large-Scale Dynamic Characterization of Flaky Tests in Quantum Software: The Qiskit Terra Case Study
Dongchan Kim, Hamidreza Khoramrokh, Lei Zhang +1
Flaky tests, tests that pass or fail nondeterministically without changes to code or environment, pose a threat to software reliability. While classical software engineering has de…
Assessing how hyperparameters impact Large Language Models' sarcasm detection performance
Montgomery Gole, Andriy Miranskyy
Sarcasm detection is challenging for both humans and machines. This work explores how model characteristics impact sarcasm detection in OpenAI's GPT, and Meta's Llama-2 models, giv…
Automating Quantum Software Maintenance: Flakiness Detection and Root Cause Analysis
Janakan Sivaloganathan, Ainaz Jamshidi, Andriy Miranskyy +1
Flaky tests, which pass or fail inconsistently without code changes, are a major challenge in software engineering in general and in quantum software engineering in particular due…
Automated flakiness detection in quantum software bug reports
Lei Zhang, Andriy Miranskyy
A flaky test yields inconsistent results upon repetition, posing a significant challenge to software developers. An extensive study of their presence and characteristics has been d…
On Using Quasirandom Sequences in Machine Learning for Model Weight Initialization
Andriy Miranskyy, Adam Sorrenti, Viral Thakar
The effectiveness of training neural networks directly impacts computational costs, resource allocation, and model development timelines in machine learning applications. An optimi…
Comparing Algorithms for Loading Classical Datasets into Quantum Memory
Andriy Miranskyy, Mushahid Khan, Udson Mendes
Quantum computers are gaining importance in various applications like quantum machine learning and quantum signal processing. These applications face significant challenges in load…
On Sarcasm Detection with OpenAI GPT-based Models
Montgomery Gole, Williams-Paul Nwadiugwu, Andriy Miranskyy
Sarcasm is a form of irony that requires readers or listeners to interpret its intended meaning by considering context and social cues. Machine learning classification models have…