76 citations · 278 across the 39 of their papers we have counts for
6 papers · 1 filter
CodeLL: A Lifelong Learning Dataset to Support the Co-Evolution of Data and Language Models of Code
Martin Weyssow, Claudio Di Sipio, Davide Di Ruscio +1
Motivated by recent work on lifelong learning applications for language models (LMs) of code, we introduce CodeLL, a lifelong learning dataset focused on code changes. Our contribu…
Toward Optimal Psychological Functioning in AI-driven Software Engineering Tasks: The SEWELL-CARE Assessment Framework
Oussama Ben Sghaier, Jean-Sebastien Boudrias, Houari Sahraoui
In the field of software engineering, there has been a shift towards utilizing various artificial intelligence techniques to address challenges and create innovative tools. These s…
Unity is Strength: Cross-Task Knowledge Distillation to Improve Code Review Generation
Oussama Ben Sghaier, Lucas Maes, Houari Sahraoui
Code review is a fundamental process in software development that plays a critical role in ensuring code quality and reducing the likelihood of errors and bugs. However, code revie…
Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models
Martin Weyssow, Xin Zhou, Kisub Kim +2
Large language models (LLMs) demonstrate impressive capabilities to generate accurate code snippets given natural language intents in a zero-shot manner, i.e., without the need for…
Fingerprinting and Building Large Reproducible Datasets
Romain Lefeuvre, Jessie Galasso, Benoit Combemale +2
Obtaining a relevant dataset is central to conducting empirical studies in software engineering. However, in the context of mining software repositories, the lack of appropriate to…
On the Usage of Continual Learning for Out-of-Distribution Generalization in Pre-trained Language Models of Code
Martin Weyssow, Xin Zhou, Kisub Kim +2
Pre-trained language models (PLMs) have become a prevalent technique in deep learning for code, utilizing a two-stage pre-training and fine-tuning procedure to acquire general know…