3 citations · 6 across the 4 of their papers we have counts for
4 papers
Bugs in Large Language Models Generated Code: An Empirical Study
Florian Tambon, Arghavan Moradi Dakhel, Amin Nikanjam +3
Large Language Models (LLMs) for code have gained significant attention recently. They can generate code in different programming languages based on provided prompts, fulfilling a…
Deep Learning Model Reuse in the HuggingFace Community: Challenges, Benefit and Trends
Mina Taraghi, Gianolli Dorcelus, Armstrong Foundjem +2
The ubiquity of large-scale Pre-Trained Models (PTMs) is on the rise, sparking interest in model hubs, and dedicated platforms for hosting PTMs. Despite this trend, a comprehensive…
Bug Characterization in Machine Learning-based Systems
Mohammad Mehdi Morovati, Amin Nikanjam, Florian Tambon +3
Rapid growth of applying Machine Learning (ML) in different domains, especially in safety-critical areas, increases the need for reliable ML components, i.e., a software component…
Mutation Testing of Deep Reinforcement Learning Based on Real Faults
Florian Tambon, Vahid Majdinasab, Amin Nikanjam +2
Testing Deep Learning (DL) systems is a complex task as they do not behave like traditional systems would, notably because of their stochastic nature. Nonetheless, being able to ad…