Reusing deep learning models: Challenges and directions in software engineering

JC Davis, P Jajal, W Jiang… - 2023 IEEE John …, 2023 - ieeexplore.ieee.org
Deep neural networks (DNNs) achieve state-of-the-art performance in many areas, including
computer vision, system configuration, and question-answering. However, DNNs are …

An empirical study of pre-trained model reuse in the hugging face deep learning model registry

W Jiang, N Synovic, M Hyatt… - 2023 IEEE/ACM 45th …, 2023 - ieeexplore.ieee.org
Deep Neural Networks (DNNs) are being adopted as components in software systems.
Creating and specializing DNNs from scratch has grown increasingly difficult as state-of-the …

Signing in four public software package registries: Quantity, quality, and influencing factors

TR Schorlemmer, KG Kalu, L Chigges… - … IEEE Symposium on …, 2024 - ieeexplore.ieee.org
Many software applications incorporate open-source third-party packages distributed by
public package registries. Guaranteeing authorship along this supply chain is a challenge …

Challenges and practices of deep learning model reengineering: A case study on computer vision

W Jiang, V Banna, N Vivek, A Goel, N Synovic… - Empirical Software …, 2024 - Springer
Context Many engineering organizations are reimplementing and extending deep neural
networks from the research community. We describe this process as deep learning model …

Exploring naming conventions (and defects) of pre-trained deep learning models in hugging face and other model hubs

W Jiang, C Cheung, GK Thiruvathukal… - arXiv preprint arXiv …, 2023 - arxiv.org
As innovation in deep learning continues, many engineers want to adopt Pre-Trained deep
learning Models (PTMs) as components in computer systems. PTMs are part of a research-to …

Peatmoss: A dataset and initial analysis of pre-trained models in open-source software

W Jiang, J Yasmin, J Jones, N Synovic… - 2024 IEEE/ACM 21st …, 2024 - ieeexplore.ieee.org
The development and training of deep learning models have become increasingly costly
and complex. Consequently, software engineers are adopting pre-trained models (PTMs) for …

Ecosystem of Large Language Models for Code

Z Yang, J Shi, P Devanbu, D Lo - arXiv preprint arXiv:2405.16746, 2024 - arxiv.org
The availability of vast amounts of publicly accessible data of source code and the advances
in modern language models, coupled with increasing computational resources, have led to …

Contrastive knowledge amalgamation for unsupervised image classification

S Gao, Y Fu, K Liu, Y Han - International Conference on Artificial Neural …, 2023 - Springer
Abstract Knowledge amalgamation (KA) aims to learn a compact student model to handle
the joint objective from multiple teacher models that are specialized for their own tasks …

[PDF][PDF] Naming Practices of Pre-Trained Models in Hugging Face

W Jiang, C Cheung, M Kim, H Kim… - arXiv preprint arXiv …, 2024 - wenxin-jiang.github.io
Authors' addresses: Wenxin Jiang, Purdue University, West Lafayette, IN, USA, jiang784@
purdue. edu; Chingwo Cheung, Purdue University, West Lafayette, IN, USA, cheung59 …

CrashJS: A NodeJS Benchmark for Automated Crash Reproduction

P Oliver, J Dietrich, C Anslow… - 2024 IEEE/ACM 21st …, 2024 - ieeexplore.ieee.org
Software bugs often lead to software crashes, which cost US companies upwards of $2.08
trillion annually. Automated Crash Reproduction (ACR) aims to generate unit tests that …