Publications

  1. Naming Practices of Pre-Trained Models in Hugging Face.
    Jiang, Cheung, Kim, Kim, Thiruvathukal, Davis.
    arXiv 2024.

  1. PeaTMOSS: Mining Pre-Trained Models in Open-Source Software.
    Jiang, Yasmin, Jones, Synovic, Kuo, Bielanski, Tian, Thiruvathukal, and Davis.
    Proceedings of the 21th International Conference on Mining Software Repositories (MSR) 2024.

  2. Reusing Deep Learning Models: Challenges and Directions in Software Engineering.
    Davis, Jajal, Jiang, Schorlemmer, Synovic, and Thiruvathukal.
    Proceedings of the IEEE John Vincent Atanasoff Symposium on Modern Computing (JVA) 2023.

  3. Analysis of Failures and Risks in Deep Learning Model Converters: A Case Study in the ONNX Ecosystem.
    Jajal, Jiang, Tewari, Woo, Lu, Thiruvathukal, and Davis.
    arXiv 2023.

  4. Challenges and Practices of Deep Learning Model Reengineering: A Case Study on Computer Vision.
    Jiang, Banna, Vivek, Goel, Synovic, Thiruvathukal, and Davis.
    arXiv 2023.

  5. PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages.
    Jiang, Synovic, Jajal, Schorlemmer, Tewari, Pareek, Thiruvathukal, and Davis. Proceedings of the 20th International Conference on Mining Software Repositories (MSR) 2023.

  6. An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry.
    Jiang, Synovic, Hyatt, Schorlemmer, Sethi, Lu, Thiruvathukal, and Davis. Proceedings of the 45th International Conference on Software Engineering (ICSE) 2023.

  7. Discrepancies among Pre-trained Deep Neural Networks: A New Threat to Model Zoo Reliability.
    Montes, Peerapatanapokin, Schultz, Guo, Jiang, and Davis.
    Proceedings of the 30th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering: Ideas, Visions, and Reflections track (ESEC/FSE-IVR) 2022.

  8. An Empirical Study of Artifacts and Security Practices in the Pre-trained Model Supply Chain.
    Jiang, Synovic, Sethi, Indarapu, Hyatt, Schorlemmer, Thiruvathukal, and Davis.
    Proceedings of the 1st ACM Workshop on Software Supply Chain Offensive Research and Ecosystem Defenses (SCORED) 2022.

  9. Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics.
    Synovic, Hyatt, Sethi, Thota, Shilpika, Miller, Jiang, Pinderski, Läufer, Hayward, Klingensmith, Davis, and Thiruvathukal.
    Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering: Demonstrations track (ASE-Demonstrations) 2022.

  10. An Experience Report on Machine Learning Reproducibility: Guidance for Practitioners and TensorFlow Model Garden Contributors.
    Banna, Chinnakotla, Yan, Vegesana, Vivek, Krishnappa, Jiang, Lu, Thiruvathukal, and Davis.
    arXiv 2021.

  11. Establishing Trust in Vehicle-to-Vehicle Coordination: A Sensor Fusion Approach.
    Veselsky, West, Ahlgren, Goel, Jiang, Lee, Kim, Davis, Thiruvathukal, and Klingensmith.
    Proceedings of the 23rd Annual International Workshop on Mobile Computing Systems and Application (HotMobile) 2022.