DriveGPT: Scaling Autoregressive Behavior Models for Driving
from Arxiv Papers Hosted by Igor Melnyk
DriveGPT is a scalable transformer model for autonomous driving, enhancing decision-making and prediction through extensive training data, outperforming existing models in complex real-world scenarios. https://arxiv.org/abs//2412.14415 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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How long is this episode of Arxiv Papers?
This episode is 19 minutes long.
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This episode was published on December 20, 2024.
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