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Kouemo Ngassom, S., Moradi Dakhel, A., Tambon, F., & Khomh, F. (juillet 2024). Chain of Targeted Verification Questions to Improve the Reliability of Code Generated by LLMs [Communication écrite]. 1st ACM International Conference on AI-Powered Software (ALWARE 2024), Porto de Galinhas, Brazil. Lien externe
Morovati, M. M., Nikanjam, A., Tambon, F., Khomh, F., & Jiang, Z. M. (2024). Bug characterization in machine learning-based systems. Empirical Software Engineering, 29(1), 14 (29 pages). Lien externe
Morovati, M. M., Tambon, F., Taraghi, M., Nikanjam, A., & Khomh, F. (2024). Common challenges of deep reinforcement learning applications development: an empirical study. Empirical Software Engineering, 29, 95 (33 pages). Lien externe
Tambon, F. (2024). GIST: Generated Inputs Sets Transferability in Deep Learning (Part 2) [Ensemble de données]. Lien externe
Tambon, F., Nikanjam, A., An, L., Khomh, F., & Antoniol, G. (2024). Silent bugs in deep learning frameworks: an empirical study of Keras and TensorFlow. Empirical Software Engineering, 29(1), 10 (34 pages). Lien externe
Taraghi, M., Dorcelus, G., Foundjem, A., Tambon, F., & Khomh, F. (mars 2024). Deep Learning Model Reuse in the HuggingFace Community: Challenges, Benefit and Trends [Communication écrite]. 31st IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2024), Rovaniemi, Finland. Lien externe
