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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.
iTAG flips the script on causally-annotated text generation, achieving both natural language and high annotation accuracy by treating the causal graph as the target and iteratively refining concept selection.
