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The system is a single 2B vision-language model that answers multiple-choice questions about ten-minute egocentric videos in one greedy forward pass, and reaches 89% of the accuracy of the large agentic pipeline using 1.1% of its parameters.
This submission to the EgoProactive track of the ECCV 2026 Wearable AI Challenge is presented, which ranked first in the large-model division and second in the<=2B division, suggesting that visual grounding is more important than annotation volume for this task.