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Nicholas Synovic
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Journal Articles
- 2024
- [j1]Wenxin Jiang
, Vishnu Banna
Challenges and practices of deep learning model reengineering: A case study on computer vision. Empir. Softw. Eng. 29(6): 142 (2024)
Conference and Workshop Papers
- 2024
- [c8]Caleb Tung, Nicholas Eliopoulos, Purvish Jajal, Gowri Ramshankar, Cheng-Yun Yang, Nicholas Synovic, Xuecen Zhang, Vipin Chaudhary, George K. Thiruvathukal, Yung-Hsiang Lu:
An automated approach for improving the inference latency and energy efficiency of pretrained CNNs by removing irrelevant pixels with focused convolutions. ASPDAC 2024: 890-895 - [c7]Jason Jones
What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claims. ESEM 2024: 13-24 - [c6]Wenxin Jiang
PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software. MSR 2024: 431-443 - 2023
- [c5]Wenxin Jiang, Nicholas Synovic, Matt Hyatt, Taylor R. Schorlemmer, Rohan Sethi, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis:
An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry. ICSE 2023: 2463-2475 - [c4]James C. Davis, Purvish Jajal, Wenxin Jiang, Taylor R. Schorlemmer, Nicholas Synovic, George K. Thiruvathukal:
Reusing Deep Learning Models: Challenges and Directions in Software Engineering. JVA 2023: 17-30 - [c3]Wenxin Jiang, Nicholas Synovic, Purvish Jajal, Taylor R. Schorlemmer, Arav Tewari, Bhavesh Pareek, George K. Thiruvathukal, James C. Davis:
PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages. MSR 2023: 57-61 - 2022
- [c2]Nicholas M. Synovic
Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics. ASE 2022: 167:1-167:4 - [c1]Wenxin Jiang
An Empirical Study of Artifacts and Security Risks in the Pre-trained Model Supply Chain. SCORED@CCS 2022: 105-114
Informal and Other Publications
- 2024
- [i9]Wenxin Jiang, Jerin Yasmin, Jason Jones, Nicholas Synovic, Jiashen Kuo, Nathaniel Bielanski, Yuan Tian, George K. Thiruvathukal, James C. Davis:
PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software. CoRR abs/2402.00699 (2024) - [i8]James C. Davis, Purvish Jajal, Wenxin Jiang, Taylor R. Schorlemmer, Nicholas Synovic, George K. Thiruvathukal:
Reusing Deep Learning Models: Challenges and Directions in Software Engineering. CoRR abs/2404.16688 (2024) - [i7]Jason Jones, Wenxin Jiang, Nicholas Synovic, George K. Thiruvathukal, James C. Davis:
What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claims. CoRR abs/2406.08205 (2024) - 2023
- [i6]Wenxin Jiang, Nicholas Synovic, Matt Hyatt, Taylor R. Schorlemmer, Rohan Sethi, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis:
An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry. CoRR abs/2303.02552 (2023) - [i5]Wenxin Jiang, Vishnu Banna, Naveen Vivek, Abhinav Goel, Nicholas Synovic, George K. Thiruvathukal, James C. Davis:
Challenges and Practices of Deep Learning Model Reengineering: A Case Study on Computer Vision. CoRR abs/2303.07476 (2023) - [i4]Wenxin Jiang, Nicholas Synovic, Purvish Jajal, Taylor R. Schorlemmer, Arav Tewari, Bhavesh Pareek, George K. Thiruvathukal, James C. Davis:
PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages. CoRR abs/2303.08934 (2023) - [i3]Wenxin Jiang, Jason Jones, Jerin Yasmin, Nicholas Synovic, Rajeev Sashti, Sophie Chen, George K. Thiruvathukal, Yuan Tian, James C. Davis:
PeaTMOSS: Mining Pre-Trained Models in Open-Source Software. CoRR abs/2310.03620 (2023) - [i2]Caleb Tung, Nicholas Eliopoulos
An automated approach for improving the inference latency and energy efficiency of pretrained CNNs by removing irrelevant pixels with focused convolutions. CoRR abs/2310.07782 (2023) - 2022
- [i1]Nicholas Synovic, Matt Hyatt
Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics. CoRR abs/2207.11767 (2022)
Coauthor Index
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