Seongwon Cho — accepted AI-conference papers

2026

BINDER: Instantly Adaptive Mobile Manipulation with Open-Vocabulary Commands

Seongwon Cho, Daechul Ahn, Donghyun Shin, Hyeonbeom Choi, San Kim, Jonghyun Choi

ICRA 2026poster

Open-vocabulary mobile manipulation (OVMM) requires robots to follow language instructions, navigate, and manipulate while updating their world representation as the environment changes dynamically. However, most prior works update their world representation only at discrete milestones, such as wayp…

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2026

SCALE: Self-uncertainty Conditioned Adaptive Looking and Execution for Vision-Language-Action Models

Hyeonbeom Choi, Daechul Ahn, Youhan Lee, Taewook Kang, Seongwon Cho, Jonghyun Choi

ICML 2026spotlight

Vision-Language-Action (VLA) models have emerged as a promising paradigm for general-purpose robotic control, with test-time scaling (TTS) gaining attention to enhance robustness beyond training. However, existing TTS methods for VLAs require additional training, verifiers, and multiple forward pass…

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