4 citations · 10 across the 11 of their papers we have counts for
10 papers · 1 filter
An Empirical Investigation of Pre-Trained Deep Learning Model Reuse in the Scientific Process
Nicholas M. Synovic, Karolina Ryzka, Alessandra V. Vellucci Solari +3
Deep learning has achieved recognition for its impact within natural sciences, yet the prohibitive financial and technical cost of training models from scratch inhibit adoption. Fo…
Process-based Indicators of Vulnerability Re-Introducing Code Changes: An Exploratory Case Study
Samiha Shimmi, Nicholas M. Synovic, Mona Rahimi +1
Software vulnerabilities often persist or re-emerge even after being fixed, revealing the complex interplay between code evolution and socio-technical factors. While source code me…
What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claims
Jason Jones, Wenxin Jiang, Nicholas Synovic +2
Background: Collaborative Software Package Registries (SPRs) are an integral part of the software supply chain. Much engineering work synthesizes SPR package into applications. Pri…
Reusing Deep Learning Models: Challenges and Directions in Software Engineering
James C. Davis, Purvish Jajal, Wenxin Jiang +3
Deep neural networks (DNNs) achieve state-of-the-art performance in many areas, including computer vision, system configuration, and question-answering. However, DNNs are expensive…
PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software
Wenxin Jiang, Jerin Yasmin, Jason Jones +6
The development and training of deep learning models have become increasingly costly and complex. Consequently, software engineers are adopting pre-trained models (PTMs) for their…
PeaTMOSS: Mining Pre-Trained Models in Open-Source Software
Wenxin Jiang, Jason Jones, Jerin Yasmin +6
Developing and training deep learning models is expensive, so software engineers have begun to reuse pre-trained deep learning models (PTMs) and fine-tune them for downstream tasks…