Explainability of Deep Models

The concept of explainability has several facets and the need for explainability is strong in safety-critical applications such as autonomous driving. We investigate methods providing post-hoc explanations to black-box systems, and approaches to directly design more interpretable models.

Selected publications

  1. 2026

  2. DRIV-EX: Counterfactual Explanations for Driving LLMs
    Amaia Cardiel, Éloi Zablocki, Elias Ramzi, Eric Gaussier
    ACL Findings 2026
  3. GIFT: A Framework for Global Interpretable Faithful Textual Explanations of Vision Classifiers
    Éloi Zablocki*, Valentin Gerard*, Amaia Cardiel, Eric Gaussier, Matthieu Cord, Eduardo Valle
    TMLR 2026Featured Certification
  4. 2025

  5. Analyzing Fine-tuning Representation Shift for Multimodal LLMs Steering alignment
    Pegah Khayatan*, Mustafa Shukor*, Jayneel Parekh*, Matthieu Cord
    ICCV 2025
  6. ToddlerDiffusion: Interactive Structured Image Generation with Cascaded Schrödinger Bridge
    Eslam Abdelrahman, Liangbing Zhao, Vincent Tao Hu, Matthieu Cord, Patrick Perez, Mohamed Elhoseiny
    ICLR 2025
  7. 2024

  8. A Concept-Based Explainability Framework for Large Multimodal Models
    Jayneel Parekh, Pegah Khayatan, Mustafa Shukor, Alasdair Newson, Matthieu Cord
    NeurIPS 2024
  9. What Makes Multimodal In-Context Learning Work?
    Folco Bertini Baldassini, Mustafa Shukor, Matthieu Cord, Laure Soulier, Benjamin Piwowarski
    CVPR Workshop on Prompting in Vision 2024
  10. 2023

  11. OCTET: Object-aware Counterfactual Explanations
    Mehdi Zemni, Mickaël Chen, Éloi Zablocki, Hédi Ben-Younes, Patrick Pérez, Matthieu Cord
    CVPR 2023
  12. 2022

  13. STEEX: Steering Counterfactual Explanations with Semantics
    Paul Jacob, Éloi Zablocki, Hédi Ben-Younes, Mickaël Chen, Patrick Pérez, Matthieu Cord
    ECCV 2022
  14. Explainability of deep vision-based autonomous driving systems: Review and challenges
    Éloi Zablocki*, Hédi Ben-Younes*, Patrick Pérez, Matthieu Cord
    IJCV 2022
  15. Driving behavior explanation with multi-level fusion
    Hédi Ben-Younes*, Éloi Zablocki*, Patrick Pérez, Matthieu Cord
    Pattern Recognition 2022