Florian Tambon

According to our database, Florian Tambon authored at least 16 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2026

Inferring Code Correctness from Specification.

Florian Tambon, Mike Papadakis

CoRR, May, 2026

2025

Bugs in large language models generated code: an empirical study.

Florian Tambon, Arghavan Moradi Dakhel, Amin Nikanjam, Foutse Khomh, Michel C. Desmarais, Giuliano Antoniol

Empir. Softw. Eng., June, 2025

On the Robustness of Tabular Foundation Models: Test-Time Attacks and In-Context Defenses.

Mohamed Djilani, Thibault Simonetto, Karim Tit, Florian Tambon, Paul Récamier, Salah Ghamizi, Maxime Cordy, Mike Papadakis

CoRR, June, 2025

Towards Collecting Real-Time Vigilance Measures for Adaptive Training in Safety-Critical Domains.

Alexandre Marois, Andra Mahu, Jonay Ramon Alaman, Florian Tambon, Yann Pequignot, Tanya S. Paul, Benoit Ouellette, Philippe Doyon-Poulin

Proceedings of the HCI International 2025 - Late Breaking Papers, 2025

2024

<i>GIST</i>: Generated Inputs Sets Transferability in Deep Learning.

Florian Tambon, Foutse Khomh, Giuliano Antoniol

ACM Trans. Softw. Eng. Methodol., November, 2024

Common challenges of deep reinforcement learning applications development: an empirical study.

Mohammad Mehdi Morovati, Florian Tambon, Mina Taraghi, Amin Nikanjam, Foutse Khomh

Empir. Softw. Eng., July, 2024

Silent bugs in deep learning frameworks: an empirical study of Keras and TensorFlow.

Florian Tambon, Amin Nikanjam, Le An, Foutse Khomh, Giuliano Antoniol

Empir. Softw. Eng., February, 2024

Bug characterization in machine learning-based systems.

Mohammad Mehdi Morovati, Amin Nikanjam, Florian Tambon, Foutse Khomh, Zhen Ming (Jack) Jiang

Empir. Softw. Eng., February, 2024

Assessing Programming Task Difficulty for Efficient Evaluation of Large Language Models.

Florian Tambon, Amin Nikanjam, Foutse Khomh, Giuliano Antoniol

CoRR, 2024

Deep Learning Model Reuse in the HuggingFace Community: Challenges, Benefit and Trends.

Mina Taraghi, Gianolli Dorcelus, Armstrong Foundjem, Florian Tambon, Foutse Khomh

Proceedings of the IEEE International Conference on Software Analysis, 2024

Chain of Targeted Verification Questions to Improve the Reliability of Code Generated by LLMs.

Sylvain Kouemo Ngassom, Arghavan Moradi Dakhel, Florian Tambon, Foutse Khomh

Proceedings of the 1st ACM International Conference on AI-Powered Software, 2024

2023

A probabilistic framework for mutation testing in deep neural networks.

Florian Tambon, Foutse Khomh, Giuliano Antoniol

Inf. Softw. Technol., 2023

GIST: Generated Inputs Sets Transferability in Deep Learning.

Florian Tambon, Foutse Khomh, Giuliano Antoniol

CoRR, 2023

Mutation Testing of Deep Reinforcement Learning Based on Real Faults.

Florian Tambon, Vahid Majdinasab, Amin Nikanjam, Foutse Khomh, Giuliano Antoniol

Proceedings of the IEEE Conference on Software Testing, Verification and Validation, 2023

2022

How to certify machine learning based safety-critical systems? A systematic literature review.

Florian Tambon, Gabriel Laberge, Le An, Amin Nikanjam, Paulina Stevia Nouwou Mindom, Yann Pequignot, Foutse Khomh, Giulio Antoniol, Ettore Merlo, François Laviolette

Autom. Softw. Eng., 2022

2021

HOMRS: High Order Metamorphic Relations Selector for Deep Neural Networks.

Florian Tambon, Giulio Antoniol, Foutse Khomh

CoRR, 2021