| An empirical study of pre-trained model reuse in the hugging face deep learning model registry W Jiang, N Synovic, M Hyatt, TR Schorlemmer, R Sethi, YH Lu, ... arXiv preprint arXiv:2303.02552, 2023 | 33 | 2023 |
| An empirical study of artifacts and security risks in the pre-trained model supply chain W Jiang, N Synovic, R Sethi, A Indarapu, M Hyatt, TR Schorlemmer, ... Proceedings of the 2022 ACM Workshop on Software Supply Chain Offensive …, 2022 | 15 | 2022 |
| Reusing Deep Learning Models: Challenges and Directions in Software Engineering JC Davis, P Jajal, W Jiang, TR Schorlemmer, N Synovic, ... | 8 | 2023 |
| PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages W Jiang, N Synovic, P Jajal, TR Schorlemmer, A Tewari, B Pareek, ... arXiv preprint arXiv:2303.08934, 2023 | 7 | 2023 |
| Challenges and practices of deep learning model reengineering: A case study on computer vision W Jiang, V Banna, N Vivek, A Goel, N Synovic, GK Thiruvathukal, ... arXiv preprint arXiv:2303.07476, 2023 | 5 | 2023 |
| Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics NM Synovic, M Hyatt, R Sethi, S Thota, Shilpika, AJ Miller, W Jiang, ... Proceedings of the 37th IEEE/ACM International Conference on Automated …, 2022 | 2 | 2022 |
| Metrics Pipeline (Codename): An Analytics and Visualization Pipeline for Software Quality Metrics N Synovic, E Amobi, E Greve, S Von Hatten, A Pinderski, S Rodriguez, ... | | 2021 |
| Toward a containerized pipeline for longitudinal analysis of open-source software projects A Miller, G Thiruvathukal, K Laufer, E Amobi, S Higgins, L Maliakal, ... | | 2020 |
