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Extracting and clustering independent components from EEG data reveals stable neural signatures of emergency braking, enabling more accurate braking intensity prediction.
Continual learning methods for Video-LLMs face a fundamental trade-off: mitigating catastrophic forgetting often comes at the cost of generalization or prohibitive computational overhead.
