1 citations · 1 across the 6 of their papers we have counts for
4 papers · 1 filter
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-…
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…
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…