Author

Seonghoon Yu

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Preprint Oct 2026

When to Switch: Reliable Action-Chunk Extension for Vision-Language-Action Models

Vision-Language-Action (VLA) models serve as unified policies for robotic manipulation, yet their expensive inference forces robots to pause between policy calls, resulting in stop-and-go execution that interrupts smooth motion and prolongs task completion. Extending the action chunk reduces policy calls and hence thes...

Seonghoon Yu, Dongwon Kim, Hyungrok Jung et al. · 0 citations

#artificial intelligence Preprint Aug 2026

Cost-efficient Active Learning for Referring Image Segmentation and Grounding

This work formulates active learning for VG under the realistic setting where only raw images are available without accompanying text, and introduces Referred Region Ambiguity, a new acquisition function that measures whether the model's confidence collapses onto a single region or disperses across multiple candidates.

Junbeom Hong, Seonghoon Yu, Hyungsik Jung et al. · 0 citations