| Flexible and context-specific AI explainability: a multidisciplinary approach V Beaudouin, I Bloch, D Bounie, S Clémençon, F d'Alché-Buc, J Eagan, ... arXiv preprint arXiv:2003.07703, 2020 | 100 | 2020 |
| A Framework to Learn with Interpretation J Parekh, P Mozharovskyi, F d'Alché-Buc Advances in Neural Information Processing Systems (NeurIPS 2021), 2020 | 44 | 2020 |
| Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF J Parekh, S Parekh, P Mozharovskyi, F d'Alché-Buc, G Richard Advances in Neural Information Processing Systems (NeurIPS 2022), 2022 | 23 | 2022 |
| Identifying the" Right" Level of Explanation in a given Situation V Beaudouin, I Bloch, D Bounie, S Clémençon, F d'Alché-Buc, JR Eagan, ... 1st International Workshop on New Foundations for Human-Centered AI (NeHuAI …, 2020 | 15 | 2020 |
| Speech-to-singing conversion in an encoder-decoder framework J Parekh, P Rao, YH Yang IEEE International Conference on Acoustics, Speech and Signal Processing …, 2020 | 14 | 2020 |
| A Concept-Based Explainability Framework for Large Multimodal Models J Parekh, P Khayatan, M Shukor, A Newson, M Cord Advances in Neural Information Processing Systems (NeurIPS 2024), 2024 | 12 | 2024 |
| Tackling Interpretability in Audio Classification Networks with Non-negative Matrix Factorization J Parekh, S Parekh, P Mozharovskyi, G Richard, F d'Alché-Buc IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP), 2023 | 10 | 2023 |
| Flexible and context-specific AI explainability: A multidisciplinary approach, 2020, CoRR V Beaudouin, I Bloch, D Bounie, S Clémençon, F d’Alché-Buc, J Eagan, ... arXiv preprint arXiv:2003.07703, 0 | 9 | |
| Deep pairwise classification and ranking for predicting media interestingness J Parekh, H Tibrewal, S Parekh ACM International Conference on Multimedia Retrieval (ACM ICMR) 2018, 428-433, 2018 | 6 | 2018 |
| The IITB Predicting Media Interestingness System for MediaEval 2017. J Parekh, H Tibrewal, S Parekh MediaEval, 2017 | 4 | 2017 |
| The MLPBOON Predicting Media Interestingness System for MediaEval 2016. J Parekh, S Parekh MediaEval, 2016 | 3 | 2016 |
| Analyzing Fine-tuning Representation Shift for Multimodal LLMs Steering alignment P Khayatan*, M Shukor*, J Parekh*, M Cord arXiv preprint arXiv:2501.03012, 2025 | | 2025 |
| One Wave to Explain Them All: A Unifying Perspective on Post-hoc Explainability G Kasmi, A Brunetto, T Fel, J Parekh arXiv preprint arXiv:2410.01482, 2024 | | 2024 |
| Restyling Unsupervised Concept Based Interpretable Networks with Generative Models J Parekh*, Q Bouniot*, P Mozharovskyi, A Newson, F d'Alché-Buc International Conference on Learning Representations (ICLR 2025), 2024 | | 2024 |
| Un cadre flexible pour l'apprentissage automatique interprétable: application à la classification d'images et d'audio J Parekh Institut Polytechnique de Paris, 2023 | | 2023 |
| A Flexible Framework for Interpretable Machine Learning: application to image and audio classification J Parekh Institut polytechnique de Paris, 2023 | | 2023 |
| Conceptualize Any Network: A Concept Extraction Framework for Holistic Interpretability of Image Classifiers H Moghaddam, Q Bouniot, J Parekh, P Mozharovskyi, F d'Alché-Buc | | |
Florence d'Alché-BucTélécom Paris, Institut Polytechnique de ParisVerified email at telecom-paris.fr
