Publications

Refereed Conference/Journal Publications

1. PeaTMOSS: A Dataset and Initial Analysis of 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. Challenges and Practices of Deep Learning Model Reengineering: A Case Study on Computer Vision.
   Jiang, Banna, Vivek, Goel, Synovic, Thiruvathukal, and Davis.
   Empirical Software Engineering (EMSE) 2024.

3. What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claims.
   Jones, Jiang, Synovic, Thiruvathukal, and Davis. Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) 2024.

4. Interoperability in Deep Learning: A User Survey and Failure Analysis of ONNX Model Converters.
   Jajal, Jiang, Tewari, Woo, Lu, Thiruvathukal, and Davis.
   Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) 2024.

5. 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.
   

6. 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.
   

7. 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.
   

8. 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.
   

Refereed Workshop/Demonstration Publications

1. Recommending pre-trained models for IoT devices.
   Patil, Jiang, Peng, Lugo, Kalu, LeBlanc, Smith, Heo, Aou, andDavis Proceedings of the 1st ACM Workshop on Software Supply Chain Offensive Research and Ecosystem Defenses (SCORED) 2022.
   

2. 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.
   

3. 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.
   

4. 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.
   

Technical Reports

1. Large Language Models for Energy-Efficient Code: Emerging Results and Future Directions.
   Peng, Gupte, Eliopoulos, Ho, Mantri, Deng, Jiang, Lu, Läufer, Thiruvathukal, Davis.
   arXiv 2024.
   

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

3. A Partial Replication of MaskFormer in TensorFlow on TPUs for the TensorFlow Model Garden.
   Purohit, Jiang, Ravikiran, Davis.
   arXiv 2024.
   

4. 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.