Wenxin Jiang

34 papers A* 3A 4Misc 1Journal 21Unranked 5
YearRankTypeTitle / Venue / Authors
2025 J jnl
"I see models being a whole other thing": an empirical study of pre-trained model naming conventions and a tool for enhancing naming consistency.
Empir. Softw. Eng.
Wenxin Jiang, Mingyu Kim, Chingwo Cheung, Heesoo Kim, George K. Thiruvathukal, James C. Davis
2025 J jnl
AgentHub: A Research Agenda for Agent Sharing Infrastructure.
CoRR
Erik Pautsch, Tanmay Singla, Wenxin Jiang, Huiyun Peng, Behnaz Hassanshahi, Konstantin Läufer, George K. Thiruvathukal, James C. Davis
2025 J jnl
Detecting Active and Stealthy Typosquatting Threats in Package Registries.
CoRR
Wenxin Jiang, Berk Çakar, Mikola Lysenko, James C. Davis
2025 A* conf
PickleBall: Secure Deserialization of Pickle-based Machine Learning Models.
CCS
Andreas D. Kellas, Neophytos Christou, Wenxin Jiang, Penghui Li, Laurent Simon, Yaniv David, Vasileios P. Kemerlis, James C. Davis, Junfeng Yang
2025 J jnl
PickleBall: Secure Deserialization of Pickle-based Machine Learning Models.
CoRR
Andreas D. Kellas, Neophytos Christou, Wenxin Jiang, Penghui Li, Laurent Simon, Yaniv David, Vasileios P. Kemerlis, James C. Davis, Junfeng Yang
2025 — conf
Recommending Pre-Trained Models for IoT Devices.
NIER@ICSE
Parth V. Patil, Wenxin Jiang, Huiyun Peng, Daniel Lugo, Kelechi G. Kalu, Josh LeBlanc, Lawrence Smith, Hyeonwoo Heo, Nathanael Aou, James C. Davis
2025 — conf
Recommending Pre-Trained Models for IoT Devices.
SERP4IoT
Parth V. Patil, Wenxin Jiang, Huiyun Peng, Daniel Lugo, Kelechi G. Kalu, Josh LeBlanc, Lawrence Smith, Hyeonwoo Heo, Nathanael Aou, James C. Davis
2025 J jnl
Software Dependencies 2.0: An Empirical Study of Reuse and Integration of Pre-Trained Models in Open-Source Projects.
CoRR
Jerin Yasmin, Wenxin Jiang, James C. Davis, Yuan Tian
2024 J jnl
A Partial Replication of MaskFormer in TensorFlow on TPUs for the TensorFlow Model Garden.
CoRR
Vishal Purohit, Wenxin Jiang, Akshath R. Ravikiran, James C. Davis
2024 J jnl
Challenges and practices of deep learning model reengineering: A case study on computer vision.
Empir. Softw. Eng.
Wenxin Jiang, Vishnu Banna, Naveen Vivek, Abhinav Goel, Nicholas Synovic, George K. Thiruvathukal, James C. Davis
2024 A conf
Interoperability in Deep Learning: A User Survey and Failure Analysis of ONNX Model Converters.
ISSTA
Purvish Jajal, Wenxin Jiang, Arav Tewari, Erik Kocinare, Joseph Woo, Anusha Sarraf, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis
2024 J jnl
Large Language Models for Energy-Efficient Code: Emerging Results and Future Directions.
CoRR
Huiyun Peng, Arjun Gupte, Nicholas John Eliopoulos, Chien Chou Ho, Rishi Mantri, Leo Deng, Wenxin Jiang, Yung-Hsiang Lu, Konstantin Läufer, George K. Thiruvathukal, James C. Davis
2024 A conf
PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software.
MSR
Wenxin Jiang, Jerin Yasmin, Jason Jones, Nicholas Synovic, Jiashen Kuo, Nathaniel Bielanski, Yuan Tian, George K. Thiruvathukal, James C. Davis
2024 J jnl
PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software.
CoRR
Wenxin Jiang, Jerin Yasmin, Jason Jones, Nicholas Synovic, Jiashen Kuo, Nathaniel Bielanski, Yuan Tian, George K. Thiruvathukal, James C. Davis
2024 J jnl
Recommending Pre-Trained Models for IoT Devices.
CoRR
Parth V. Patil, Wenxin Jiang, Huiyun Peng, Daniel Lugo, Kelechi G. Kalu, David J. LeBlanc, Lawrence Smith, Hyeonwoo Heo, Nathanael Aou, James C. Davis
2024 J jnl
Reusing Deep Learning Models: Challenges and Directions in Software Engineering.
CoRR
James C. Davis, Purvish Jajal, Wenxin Jiang, Taylor R. Schorlemmer, Nicholas Synovic, George K. Thiruvathukal
2024 A conf
What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claims.
ESEM
Jason Jones, Wenxin Jiang, Nicholas Synovic, George K. Thiruvathukal, James C. Davis
2024 J jnl
What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claims.
CoRR
Jason Jones, Wenxin Jiang, Nicholas Synovic, George K. Thiruvathukal, James C. Davis
2023 A* conf
An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry.
ICSE
Wenxin Jiang, Nicholas Synovic, Matt Hyatt, Taylor R. Schorlemmer, Rohan Sethi, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis
2023 J jnl
An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry.
CoRR
Wenxin Jiang, Nicholas Synovic, Matt Hyatt, Taylor R. Schorlemmer, Rohan Sethi, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis
2023 J jnl
Analysis of Failures and Risks in Deep Learning Model Converters: A Case Study in the ONNX Ecosystem.
CoRR
Purvish Jajal, Wenxin Jiang, Arav Tewari, Joseph Woo, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis
2023 J jnl
Challenges and Practices of Deep Learning Model Reengineering: A Case Study on Computer Vision.
CoRR
Wenxin Jiang, Vishnu Banna, Naveen Vivek, Abhinav Goel, Nicholas Synovic, George K. Thiruvathukal, James C. Davis
2023 J jnl
Discrepancies among Pre-trained Deep Neural Networks: A New Threat to Model Zoo Reliability.
CoRR
Diego Montes, Pongpatapee Peerapatanapokin, Jeff Schultz, Chengjun Guo, Wenxin Jiang, James C. Davis
2023 J jnl
Exploring Naming Conventions (and Defects) of Pre-trained Deep Learning Models in Hugging Face and Other Model Hubs.
CoRR
Wenxin Jiang, Chingwo Cheung, George K. Thiruvathukal, James C. Davis
2023 A conf
PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages.
MSR
Wenxin Jiang, Nicholas Synovic, Purvish Jajal, Taylor R. Schorlemmer, Arav Tewari, Bhavesh Pareek, George K. Thiruvathukal, James C. Davis
2023 J jnl
PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages.
CoRR
Wenxin Jiang, Nicholas Synovic, Purvish Jajal, Taylor R. Schorlemmer, Arav Tewari, Bhavesh Pareek, George K. Thiruvathukal, James C. Davis
2023 J jnl
PeaTMOSS: Mining Pre-Trained Models in Open-Source Software.
CoRR
Wenxin Jiang, Jason Jones, Jerin Yasmin, Nicholas Synovic, Rajeev Sashti, Sophie Chen, George K. Thiruvathukal, Yuan Tian, James C. Davis
2023 — conf
Reusing Deep Learning Models: Challenges and Directions in Software Engineering.
JVA
James C. Davis, Purvish Jajal, Wenxin Jiang, Taylor R. Schorlemmer, Nicholas Synovic, George K. Thiruvathukal
2022 — conf
An Empirical Study of Artifacts and Security Risks in the Pre-trained Model Supply Chain.
SCORED@CCS
Wenxin Jiang, Nicholas Synovic, Rohan Sethi, Aryan Indarapu, Matt Hyatt, Taylor R. Schorlemmer, George K. Thiruvathukal, James C. Davis
2022 — conf
Discrepancies among pre-trained deep neural networks: a new threat to model zoo reliability.
ESEC/SIGSOFT FSE
Diego Montes, Pongpatapee Peerapatanapokin, Jeff Schultz, Chengjun Guo, Wenxin Jiang, James C. Davis
2022 Misc conf
Establishing trust in vehicle-to-vehicle coordination: a sensor fusion approach.
HotMobile
Jakob Veselsky, Jack West, Isaac Ahlgren, George K. Thiruvathukal, Neil Klingensmith, Abhinav Goel, Wenxin Jiang, James C. Davis, Kyuin Lee, Younghyun Kim
2022 A* conf
Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics.
ASE
Nicholas M. Synovic, Matt Hyatt, Rohan Sethi, Sohini Thota, Shilpika, Allan J. Miller, Wenxin Jiang, Emmanuel S. Amobi, Austin Pinderski, Konstantin Läufer, Nicholas J. Hayward, Neil Klingensmith, James C. Davis, George K. Thiruvathukal
2022 J jnl
Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics.
CoRR
Nicholas Synovic, Matt Hyatt, Rohan Sethi, Sohini Thota, Shilpika, Allan J. Miller, Wenxin Jiang, Emmanuel S. Amobi, Austin Pinderski, Konstantin Läufer, Nicholas J. Hayward, Neil Klingensmith, James C. Davis, George K. Thiruvathukal
2021 J jnl
An Experience Report on Machine Learning Reproducibility: Guidance for Practitioners and TensorFlow Model Garden Contributors.
CoRR
Vishnu Banna, Akhil Chinnakotla, Zhengxin Yan, Anirudh Vegesana, Naveen Vivek, Kruthi Krishnappa, Wenxin Jiang, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis