Large Language Models

Explainable AI

From MIRAGE to CLEAR: Component-Level Explainable Anomaly Reasoning for Autonomous Vehicle Perception Systems

Autonomous vehicles rely on perception systems with deep neural networks for traffic sign recognition (TSR), automated lane centering (ALC), and object detection (OD). While these …

avatar
David Fernandez
•
Read more
Explainable AI

WIP: From Detection to Explanation: Using LLMs for Adversarial Scenario Analysis in Vehicles

We propose a framework that leverages Large Language Models (LLMs) for adversarial scenario analysis in Autonomous Vehicles (AVs), generating interpretable explanations for …

avatar
David Fernandez
•
Read more
Large Language Models

David vs. Goliath: A Comparative Study of Different-Sized LLMs for Code Generation in the Domain of Automotive Scenario Generation

Scenario simulation is central to testing autonomous driving systems. Scenic, a domain-specific language (DSL) for CARLA, enables precise and reproducible scenarios, but …

philipp-bauerfeind
•
Read more