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When to Switch: Reliable Action-Chunk Extension for Vision-Language-Action Models
Seonghoon Yu, Dongwon Kim, HyungRok Jung +4
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…
Cost-efficient Active Learning for Referring Image Segmentation and Grounding
Junbeom Hong, Seonghoon Yu, Hyung Rok Jung +2
Collecting natural-language referring expressions along with region annotations, such as masks or boxes, is a major bottleneck in visual grounding (VG), as annotators must write de…
Hide to See: Reasoning-prefix Masking for Visual-anchored Thinking in VLM Distillation
Seonghoon Yu, Dongjun Nam, Byung-Kwan Lee +1
Recent think-answer approaches in VLMs, such as Qwen3-VL-Thinking, boost reasoning performance by leveraging intermediate thinking steps before the final answer, but their computat…