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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FedNSAM uses global Nesterov momentum to make local flatness consistent with global flatness in federated learning, yielding tighter convergence than FedSAM and better empirical performance.
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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FedNSAM:Consistency of Local and Global Flatness for Federated Learning
FedNSAM uses global Nesterov momentum to make local flatness consistent with global flatness in federated learning, yielding tighter convergence than FedSAM and better empirical performance.