An Experience Report on Machine Learning Reproducibility: Guidance for Practitioners and TensorFlow Model Garden Contributors. - Vishnu Banna; Akhil Chinnakotla; Zhengxin Yan; Anirudh Vegesana; Naveen Vivek; Kruthi Krishnappa; Wenxin Jiang 001; Yung-Hsiang Lu; George K. Thiruvathukal; James C. Davis 001 (CoRR, 2021)

Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics. - Nicholas M. Synovic; Matt Hyatt; Rohan Sethi; Sohini Thota; Shilpika; Allan J. Miller; Wenxin Jiang 001; Emmanuel S. Amobi; Austin Pinderski; Konstantin Läufer; Nicholas J. Hayward; Neil Klingensmith; et al. (ASE, 2022)

An Empirical Study of Artifacts and Security Risks in the Pre-trained Model Supply Chain. - Wenxin Jiang 001; Nicholas Synovic; Rohan Sethi; Aryan Indarapu; Matt Hyatt; Taylor R. Schorlemmer; George K. Thiruvathukal; James C. Davis 001 (SCORED@CCS, 2022)

Discrepancies among pre-trained deep neural networks: a new threat to model zoo reliability. - Diego Montes; Pongpatapee Peerapatanapokin; Jeff Schultz; Chengjun Guo; Wenxin Jiang 001; James C. Davis 001 (ESEC/SIGSOFT FSE, 2022)

Establishing trust in vehicle-to-vehicle coordination: a sensor fusion approach. - Jakob Veselsky; Jack West; Isaac Ahlgren; George K. Thiruvathukal; Neil Klingensmith; Abhinav Goel; Wenxin Jiang 001; James C. Davis 001; Kyuin Lee; Younghyun Kim 001 (HotMobile, 2022)

An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry. - Wenxin Jiang 001; Nicholas Synovic; Matt Hyatt; Taylor R. Schorlemmer; Rohan Sethi; Yung-Hsiang Lu; George K. Thiruvathukal; James C. Davis 001 (ICSE, 2023)

Reusing Deep Learning Models: Challenges and Directions in Software Engineering. - James C. Davis 001; Purvish Jajal; Wenxin Jiang 001; Taylor R. Schorlemmer; Nicholas Synovic; George K. Thiruvathukal (JVA, 2023)

PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages. - Wenxin Jiang 001; Nicholas Synovic; Purvish Jajal; Taylor R. Schorlemmer; Arav Tewari; Bhavesh Pareek; George K. Thiruvathukal; James C. Davis 001 (MSR, 2023)

Analysis of Failures and Risks in Deep Learning Model Converters: A Case Study in the ONNX Ecosystem. - Purvish Jajal; Wenxin Jiang 001; Arav Tewari; Joseph Woo; Yung-Hsiang Lu; George K. Thiruvathukal; James C. Davis 001 (CoRR, 2023)

Exploring Naming Conventions (and Defects) of Pre-trained Deep Learning Models in Hugging Face and Other Model Hubs. - Wenxin Jiang 001; Chingwo Cheung; George K. Thiruvathukal; James C. Davis 001 (CoRR, 2023)

PeaTMOSS: Mining Pre-Trained Models in Open-Source Software. - Wenxin Jiang 001; Jason Jones; Jerin Yasmin; Nicholas Synovic; Rajeev Sashti; Sophie Chen; George K. Thiruvathukal; Yuan Tian 008; James C. Davis 001 (CoRR, 2023)

SoftwareSystemsLaboratory/PTMTorrent. - Wenxin Jiang 001; Nicholas Synovic; Purvish Jajal; Taylor R. Schorlemmer; Arav Tewari; Bhavesh Pareek; George K. Thiruvathukal; James C. Davis 001 (Zenodo, 2023)

SoftwareSystemsLaboratory/PTMTorrent. - Wenxin Jiang 001; Nicholas Synovic; Purvish Jajal; Taylor R. Schorlemmer; Arav Tewari; Bhavesh Pareek; George K. Thiruvathukal; James C. Davis 001 (Zenodo, 2023)

SoftwareSystemsLaboratory/PTMTorrent. - Wenxin Jiang 001; Nicholas Synovic; Purvish Jajal; Taylor R. Schorlemmer; Arav Tewari; Bhavesh Pareek; George K. Thiruvathukal; James C. Davis 001 (Zenodo, 2023)

SoftwareSystemsLaboratory/PTMTorrent. - Wenxin Jiang 001; Nicholas Synovic; Purvish Jajal; Taylor R. Schorlemmer; Arav Tewari; Bhavesh Pareek; George K. Thiruvathukal; James C. Davis 001 (Zenodo, 2023)

SoftwareSystemsLaboratory/PTMTorrent. - Wenxin Jiang 001; Nicholas Synovic; Purvish Jajal; Taylor R. Schorlemmer; Arav Tewari; Bhavesh Pareek; George K. Thiruvathukal; James C. Davis 001 (Zenodo, 2023)

SoftwareSystemsLaboratory/PTMTorrent. - Wenxin Jiang 001; Nicholas Synovic; Purvish Jajal; Taylor R. Schorlemmer; Arav Tewari; Bhavesh Pareek; George K. Thiruvathukal; James C. Davis 001 (Zenodo, 2023)

SoftwareSystemsLaboratory/PTMTorrent. - Wenxin Jiang 001; Nicholas Synovic; Purvish Jajal; Taylor R. Schorlemmer; Arav Tewari; Bhavesh Pareek; George K. Thiruvathukal; James C. Davis 001 (Zenodo, 2023)

An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry VM. - Wenxin Jiang 001; Nicholas Synovic; Matt Hyatt; Taylor R. Schorlemmer; Rohan Sethi; Yung-Hsiang Lu; George K. Thiruvathukal; James C. Davis 001 (Zenodo, 2023)

An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry VM. - Wenxin Jiang 001; Nicholas Synovic; Matt Hyatt; Taylor R. Schorlemmer; Rohan Sethi; Yung-Hsiang Lu; George K. Thiruvathukal; James C. Davis 001 (Zenodo, 2023)

An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry VM. - Wenxin Jiang 001; Nicholas Synovic; Matt Hyatt; Taylor R. Schorlemmer; Rohan Sethi; Yung-Hsiang Lu; George K. Thiruvathukal; James C. Davis 001 (Zenodo, 2023)

An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry VM. - Wenxin Jiang 001; Nicholas Synovic; Matt Hyatt; Taylor R. Schorlemmer; Rohan Sethi; Yung-Hsiang Lu; George K. Thiruvathukal; James C. Davis 001 (Zenodo, 2023)

What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claims. - Jason Jones; Wenxin Jiang 001; Nicholas Synovic; George K. Thiruvathukal; James C. Davis 001 (ESEM, 2024)

Interoperability in Deep Learning: A User Survey and Failure Analysis of ONNX Model Converters. - Purvish Jajal; Wenxin Jiang 001; Arav Tewari; Erik Kocinare; Joseph Woo; Anusha Sarraf; Yung-Hsiang Lu; George K. Thiruvathukal; James C. Davis 001 (ISSTA, 2024)

PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software. - Wenxin Jiang 001; Jerin Yasmin; Jason Jones; Nicholas Synovic; Jiashen Kuo; Nathaniel Bielanski; Yuan Tian 008; George K. Thiruvathukal; James C. Davis 001 (MSR, 2024)

A Partial Replication of MaskFormer in TensorFlow on TPUs for the TensorFlow Model Garden. - Vishal Purohit; Wenxin Jiang 001; Akshath R. Ravikiran; James C. Davis 001 (CoRR, 2024)

Large Language Models for Energy-Efficient Code: Emerging Results and Future Directions. - Huiyun Peng; Arjun Gupte; Nicholas John Eliopoulos; Chien Chou Ho; Rishi Mantri; Leo Deng; Wenxin Jiang 001; Yung-Hsiang Lu; Konstantin Läufer; George K. Thiruvathukal; James C. Davis 001 (CoRR, 2024)

Recommending Pre-Trained Models for IoT Devices. - Parth V. Patil; Wenxin Jiang 001; Huiyun Peng; Daniel Lugo; Kelechi G. Kalu; David J. LeBlanc; Lawrence Smith; Hyeonwoo Heo; Nathanael Aou; James C. Davis 001 (CoRR, 2024)

Challenges and practices of deep learning model reengineering: A case study on computer vision. - Wenxin Jiang 001; Vishnu Banna; Naveen Vivek; Abhinav Goel; Nicholas Synovic; George K. Thiruvathukal; James C. Davis 001 (Empir. Softw. Eng., 2024)

Recommending Pre-Trained Models for IoT Devices. - Parth V. Patil; Wenxin Jiang 001; Huiyun Peng; Daniel Lugo; Kelechi G. Kalu; Josh LeBlanc; Lawrence Smith; Hyeonwoo Heo; Nathanael Aou; James C. Davis 001 (SERP4IoT, 2025)

Detecting Active and Stealthy Typosquatting Threats in Package Registries. - Wenxin Jiang 001; Berk Çakar; Mikola Lysenko; James C. Davis 001 (CoRR, 2025)

"I see models being a whole other thing": an empirical study of pre-trained model naming conventions and a tool for enhancing naming consistency. - Wenxin Jiang 001; Mingyu Kim; Chingwo Cheung; Heesoo Kim; George K. Thiruvathukal; James C. Davis 001 (Empir. Softw. Eng., 2025)