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AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving
In this work, we propose AnoVox, the largest benchmark for ANOmaly detection in autonomous driving to date.
Exploring the Potential of Human-LLM Synergy in Advancing Qualitative Analysis: A Case Study on Mental-Illness Stigma
Qualitative analysis is a challenging, yet crucial aspect of advancing research in the field of Human-Computer Interaction (HCI).
Overconfident and Unconfident AI Hinder Human-AI Collaboration
AI transparency is a central pillar of responsible AI deployment and effective human-AI collaboration.
MUVO: A Multimodal Generative World Model for Autonomous Driving with Geometric Representations
Learning unsupervised world models for autonomous driving has the potential to improve the reasoning capabilities of today's systems dramatically.
Exploring the Potential of World Models for Anomaly Detection in Autonomous Driving
We provide a characterization of world models and relate individual components to previous works in anomaly detection to facilitate further research in the field.
