Wenxin Jiang
Orcid: 0000-0003-2608-8576Affiliations:
- Purdue University, Department of Electrical & Computer Engineering, West Lafayette, IN, USA
According to our database1,
Wenxin Jiang
authored at least 18 papers
between 2021 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Challenges and practices of deep learning model reengineering: A case study on computer vision.
Empir. Softw. Eng., November, 2024
Large Language Models for Energy-Efficient Code: Emerging Results and Future Directions.
CoRR, 2024
A Partial Replication of MaskFormer in TensorFlow on TPUs for the TensorFlow Model Garden.
CoRR, 2024
PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software.
Proceedings of the 21st IEEE/ACM International Conference on Mining Software Repositories, 2024
Interoperability in Deep Learning: A User Survey and Failure Analysis of ONNX Model Converters.
Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis, 2024
What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claims.
Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, 2024
2023
Exploring Naming Conventions (and Defects) of Pre-trained Deep Learning Models in Hugging Face and Other Model Hubs.
CoRR, 2023
Analysis of Failures and Risks in Deep Learning Model Converters: A Case Study in the ONNX Ecosystem.
CoRR, 2023
Proceedings of the 20th IEEE/ACM International Conference on Mining Software Repositories, 2023
Proceedings of the IEEE John Vincent Atanasoff International Symposium on Modern Computing, 2023
An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023
2022
Proceedings of the HotMobile '22: The 23rd International Workshop on Mobile Computing Systems and Applications, Tempe, Arizona, USA, March 9, 2022
Discrepancies among pre-trained deep neural networks: a new threat to model zoo reliability.
Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022
An Empirical Study of Artifacts and Security Risks in the Pre-trained Model Supply Chain.
Proceedings of the 2022 ACM Workshop on Software Supply Chain Offensive Research and Ecosystem Defenses, 2022
Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics.
Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, 2022
2021
An Experience Report on Machine Learning Reproducibility: Guidance for Practitioners and TensorFlow Model Garden Contributors.
CoRR, 2021