15 citations · 48 across the 8 of their papers we have counts for
9 papers
Decomposing a Recurrent Neural Network into Modules for Enabling Reusability and Replacement
Sayem Mohammad Imtiaz, Fraol Batole, Astha Singh +3
Can we take a recurrent neural network (RNN) trained to translate between languages and augment it to support a new natural language without retraining the model from scratch? Can…
An Empirical Study on the Bugs Found while Reusing Pre-trained Natural Language Processing Models
Rangeet Pan, Sumon Biswas, Mohna Chakraborty +2
In NLP, reusing pre-trained models instead of training from scratch has gained popularity; however, NLP models are mostly black boxes, very large, and often require significant res…
Manas: Mining Software Repositories to Assist AutoML
Giang Nguyen, Md Johir Islam, Rangeet Pan +1
Today deep learning is widely used for building software. A software engineering problem with deep learning is that finding an appropriate convolutional neural network (CNN) model…
Decomposing Convolutional Neural Networks into Reusable and Replaceable Modules
Rangeet Pan, Hridesh Rajan
Training from scratch is the most common way to build a Convolutional Neural Network (CNN) based model. What if we can build new CNN models by reusing parts from previously build C…
Can Program Synthesis be Used to Learn Merge Conflict Resolutions? An Empirical Analysis
Rangeet Pan, Vu Le, Nachiappan Nagappan +3
Forking structure is widespread in the open-source repositories and that causes a significant number of merge conflicts. In this paper, we study the problem of textual merge confli…
Repairing Deep Neural Networks: Fix Patterns and Challenges
Md Johirul Islam, Rangeet Pan, Giang Nguyen +1
Significant interest in applying Deep Neural Network (DNN) has fueled the need to support engineering of software that uses DNNs. Repairing software that uses DNNs is one such unmi…