2 citations · 4 across the 5 of their papers we have counts for
5 papers
Utilization of Pre-trained Language Model for Adapter-based Knowledge Transfer in Software Engineering
Iman Saberi, Fatemeh Fard, Fuxiang Chen
Software Engineering (SE) Pre-trained Language Models (PLMs), such as CodeBERT, are pre-trained on large code corpora, and their learned knowledge has shown success in transferring…
AdvFusion: Adapter-based Knowledge Transfer for Code Summarization on Code Language Models
Iman Saberi, Amirreza Esmaeili, Fatemeh Fard +1
Programming languages can benefit from one another by utilizing a pre-trained model for software engineering tasks such as code summarization and method name prediction. While full…
An Exploratory Study on Code Attention in BERT
Rishab Sharma, Fuxiang Chen, Fatemeh Fard +1
Many recent models in software engineering introduced deep neural models based on the Transformer architecture or use transformer-based Pre-trained Language Models (PLM) trained on…
LAMNER: Code Comment Generation Using Character Language Model and Named Entity Recognition
Rishab Sharma, Fuxiang Chen, Fatemeh Fard
Code comment generation is the task of generating a high-level natural language description for a given code method or function. Although researchers have been studying multiple wa…
On the Transferability of Pre-trained Language Models for Low-Resource Programming Languages
Fuxiang Chen, Fatemeh Fard, David Lo +1
A recent study by Ahmed and Devanbu reported that using a corpus of code written in multilingual datasets to fine-tune multilingual Pre-trained Language Models (PLMs) achieves high…