| 2025 | COLING | Automating Annotation Guideline Improvements using LLMs: A Case Study. | Adrien Bibal, Nathaniel Gerlek, Goran Muric, Elizabeth Boschee, Steven Fincke, Mike Ross, Steven N. Minton |
| 2022 | ACL | Is Attention Explanation? An Introduction to the Debate. | Adrien Bibal, Rmi Cardon, David Alfter, Rodrigo Wilkens, Xiaoou Wang, Thomas Franois, Patrick Watrin |
| 2022 | CIKM | AIMLAI: Advances in Interpretable Machine Learning and Artificial Intelligence. | Adrien Bibal, Tassadit Bouadi, Benot Frnay, Luis Galrraga, Jos Oramas |
| 2022 | EMNLP | Linguistic Corpus Annotation for Automatic Text Simplification Evaluation. | Rmi Cardon, Adrien Bibal, Rodrigo Wilkens, David Alfter, Magali Norr, Adeline Mller, Patrick Watrin, Thomas Franois |
| 2021 | IJCNN | Accelerating $t$-SNE using Fast Fourier Transforms and the Particle-Mesh Algorithm from Physics. | Valentin Delchevalerie, Alexandre Mayer, Adrien Bibal, Benot Frnay |
| 2021 | IJCNN | iPMDS: Interactive Probabilistic Multidimensional Scaling. | Viet Minh Vu, Adrien Bibal, Benot Frnay |
| 2021 | IJCNN | HCt-SNE: Hierarchical Constraints with t-SNE. | Viet Minh Vu, Adrien Bibal, Benot Frnay |
| 2020 | CIKM | AIMLAI'20: Third Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence. | Adrien Bibal, Tassadit Bouadi, Benot Frnay, Luis Galrraga, Jos Oramas |
| 2020 | ESANN | Explaining t-SNE Embeddings Locally by Adapting LIME. | Adrien Bibal, Viet Minh Vu, Graldin Nanfack, Benot Frnay |
| 2018 | ESANN | Finding the most interpretable MDS rotation for sparse linear models based on external features. | Adrien Bibal, Rebecca Marion, Benot Frnay |
| 2016 | ESANN | Interpretability of machine learning models and representations: an introduction. | Adrien Bibal, Benot Frnay |