1 citations · 1 across the 7 of their papers we have counts for
4 papers · 1 filter
DriveGPT: Scaling Autoregressive Behavior Models for Driving
Xin Huang, Eric M. Wolff, Paul Vernaza +13
We present DriveGPT, a scalable behavior model for autonomous driving. We model driving as a sequential decision-making task, and learn a transformer model to predict future agent…
PROFIT: A Specialized Optimizer for Deep Fine Tuning
Anirudh S Chakravarthy, Shuai Kyle Zheng, Xin Huang +4
The fine-tuning of pre-trained models has become ubiquitous in generative AI, computer vision, and robotics. Although much attention has been paid to improving the efficiency of fi…
VLMine: Long-Tail Data Mining with Vision Language Models
Mao Ye, Gregory P. Meyer, Zaiwei Zhang +4
Ensuring robust performance on long-tail examples is an important problem for many real-world applications of machine learning, such as autonomous driving. This work focuses on the…
Cohere3D: Exploiting Temporal Coherence for Unsupervised Representation Learning of Vision-based Autonomous Driving
Yichen Xie, Hongge Chen, Gregory P. Meyer +6
Due to the lack of depth cues in images, multi-frame inputs are important for the success of vision-based perception, prediction, and planning in autonomous driving. Observations f…