4 papers
DRIV-EX: Counterfactual Explanations for Driving LLMs
Amaia Cardiel, Eloi Zablocki, Elias Ramzi +1
Large language models (LLMs) are increasingly used as reasoning engines in autonomous driving, yet their decision-making remains opaque. We propose to study their decision process…
GIFT: A Framework Towards Global Interpretable Faithful Textual Explanations of Vision Classifiers
Ãloi Zablocki, Valentin Gerard, Amaia Cardiel +3
Understanding the decision processes of deep vision models is essential for their safe and trustworthy deployment in real-world settings. Existing explainability approaches, such a…
Test-time Contrastive Concepts for Open-world Semantic Segmentation with Vision-Language Models
Monika WysoczaÅska, Antonin Vobecky, Amaia Cardiel +4
Recent CLIP-like Vision-Language Models (VLMs), pre-trained on large amounts of image-text pairs to align both modalities with a simple contrastive objective, have paved the way to…
LLM-wrapper: Black-Box Semantic-Aware Adaptation of Vision-Language Models for Referring Expression Comprehension
Amaia Cardiel, Eloi Zablocki, Elias Ramzi +2
Vision Language Models (VLMs) have demonstrated remarkable capabilities in various open-vocabulary tasks, yet their zero-shot performance lags behind task-specific fine-tuned model…