1 citations · 1 across the 6 of their papers we have counts for
6 papers
PHASOR: Phase-Anchored Universal Action Representations for Humanoid Embodiments
Kihyun Kim, Chaeyun Kim, Jongho Shin +4
Learning a good action embedding space is fundamental to scalable robot policy learning, yet existing methods treat action latents as task-specific intermediates rather than first-…
EgoExo-Con: Exploring View-Invariant Video Temporal Understanding
Minjoon Jung, Junbin Xiao, Junghyun Kim +2
Do Video-LLMs have consistent temporal understanding when videos capture the same event from different viewpoints? To study this question, we introduce EgoExo-Con(sistency), a benc…
CLIP-RT: Learning Language-Conditioned Robotic Policies from Natural Language Supervision
Gi-Cheon Kang, Junghyun Kim, Kyuhwan Shim +2
Teaching robots desired skills in real-world environments remains challenging, especially for non-experts. A key bottleneck is that collecting robotic data often requires expertise…
PGA: Personalizing Grasping Agents with Single Human-Robot Interaction
Junghyun Kim, Gi-Cheon Kang, Jaein Kim +3
Language-Conditioned Robotic Grasping (LCRG) aims to develop robots that comprehend and grasp objects based on natural language instructions. While the ability to understand person…
PROGrasp: Pragmatic Human-Robot Communication for Object Grasping
Gi-Cheon Kang, Junghyun Kim, Jaein Kim +1
Interactive Object Grasping (IOG) is the task of identifying and grasping the desired object via human-robot natural language interaction. Current IOG systems assume that a human u…
GVCCI: Lifelong Learning of Visual Grounding for Language-Guided Robotic Manipulation
Junghyun Kim, Gi-Cheon Kang, Jaein Kim +2
Language-Guided Robotic Manipulation (LGRM) is a challenging task as it requires a robot to understand human instructions to manipulate everyday objects. Recent approaches in LGRM…