FSDrive uses a generated future scene frame as visual spatio-temporal CoT to improve VLA models for safer autonomous driving trajectory prediction.
SimpleLLM4AD: An end-to-end vision-language model with graph visual question answering for autonomous driving,
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
representative citing papers
HiL-OBC integrates human intervention and online Bayesian adaptation into behavior cloning for autonomous driving, reporting up to 47% driving score gains on the LangAuto-Human CARLA benchmark.
DeepSight uses parallel latent feature prediction in BEV for long-horizon world modeling and adaptive text reasoning to reach state-of-the-art closed-loop performance on the Bench2drive benchmark.
citing papers explorer
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FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving
FSDrive uses a generated future scene frame as visual spatio-temporal CoT to improve VLA models for safer autonomous driving trajectory prediction.
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Learning from Human Driving: A Human-in-the-Loop Online Behavior Cloning Framework for Autonomous Driving
HiL-OBC integrates human intervention and online Bayesian adaptation into behavior cloning for autonomous driving, reporting up to 47% driving score gains on the LangAuto-Human CARLA benchmark.
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DeepSight: Long-Horizon World Modeling via Latent States Prediction for End-to-End Autonomous Driving
DeepSight uses parallel latent feature prediction in BEV for long-horizon world modeling and adaptive text reasoning to reach state-of-the-art closed-loop performance on the Bench2drive benchmark.