3 papers
cs.RO2026
Hierarchical Latent Action Model
Hanjung Kim, Lerrel Pinto, Seon Joo Kim
Latent Action Models (LAMs) enable learning from actionless data for applications ranging from robotic control to interactive world models. However, existing LAMs typically focus o…
cs.RO2025
UniSkill: Imitating Human Videos via Cross-Embodiment Skill Representations
Hanjung Kim, Jaehyun Kang, Hyolim Kang +3
Mimicry is a fundamental learning mechanism in humans, enabling individuals to learn new tasks by observing and imitating experts. However, applying this ability to robots presents…
cs.CV2025
A Training-Free, Task-Agnostic Framework for Enhancing MLLM Performance on High-Resolution Images
Jaeseong Lee, Yeeun Choi, Heechan Choi +2
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in vision-language understanding, reasoning, and generation. However, they struggle with tasks re…