most citedAn Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry

4 citations · 6 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CR20241 cited

SoK: Analysis of Software Supply Chain Security by Establishing Secure Design Properties

Chinenye Okafor, Taylor R. Schorlemmer, Santiago Torres-Arias +1

This paper systematizes knowledge about secure software supply chain patterns. It identifies four stages of a software supply chain attack and proposes three security properties cr…

cs.SE2024

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…

cs.CR2024

Signing in Four Public Software Package Registries: Quantity, Quality, and Influencing Factors

Taylor R Schorlemmer, Kelechi G Kalu, Luke Chigges +5

Many software applications incorporate open-source third-party packages distributed by public package registries. Guaranteeing authorship along this supply chain is a challenge. Pa…

cs.SE2023

Reflecting on the Use of the Policy-Process-Product Theory in Empirical Software Engineering

Kelechi G. Kalu, Taylor R. Schorlemmer, Sophie Chen +3

The primary theory of software engineering is that an organization's Policies and Processes influence the quality of its Products. We call this the PPP Theory. Although empirical s…

cs.CR20231 cited

An Empirical Study on Using Large Language Models to Analyze Software Supply Chain Security Failures

Tanmay Singla, Dharun Anandayuvaraj, Kelechi G. Kalu +2

As we increasingly depend on software systems, the consequences of breaches in the software supply chain become more severe. High-profile cyber attacks like those on SolarWinds and…

cs.SE2023

PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages

Wenxin Jiang, Nicholas Synovic, Purvish Jajal +5

Due to the cost of developing and training deep learning models from scratch, machine learning engineers have begun to reuse pre-trained models (PTMs) and fine-tune them for downst…