51 citations · 196 across the 44 of their papers we have counts for
6 papers · 1 filter
Realistic Extreme Behavior Generation for Improved AV Testing
Robert Dyro, Matthew Foutter, Ruolin Li +4
This work introduces a framework to diagnose the strengths and shortcomings of Autonomous Vehicle (AV) collision avoidance technology with synthetic yet realistic potential collisi…
Diagnostic Runtime Monitoring with Martingales
Ali Hindy, Rachel Luo, Somrita Banerjee +3
Machine learning systems deployed in safety-critical robotics settings must be robust to distribution shifts. However, system designers must understand the cause of a distribution…
Real-Time Anomaly Detection and Reactive Planning with Large Language Models
Rohan Sinha, Amine Elhafsi, Christopher Agia +3
Foundation models, e.g., large language models (LLMs), trained on internet-scale data possess zero-shot generalization capabilities that make them a promising technology towards de…
Tokenize the World into Object-level Knowledge to Address Long-tail Events in Autonomous Driving
Ran Tian, Boyi Li, Xinshuo Weng +5
The autonomous driving industry is increasingly adopting end-to-end learning from sensory inputs to minimize human biases in system design. Traditional end-to-end driving models, h…
ZAPP! Zonotope Agreement of Prediction and Planning for Continuous-Time Collision Avoidance with Discrete-Time Dynamics
Luca Paparusso, Shreyas Kousik, Edward Schmerling +2
The past few years have seen immense progress on two fronts that are critical to safe, widespread mobile robot deployment: predicting uncertain motion of multiple agents, and plann…
Language-Image Models with 3D Understanding
Jang Hyun Cho, Boris Ivanovic, Yulong Cao +8
Multi-modal large language models (MLLMs) have shown incredible capabilities in a variety of 2D vision and language tasks. We extend MLLMs' perceptual capabilities to ground and re…