305 citations · 357 across the 27 of their papers we have counts for
4 papers · 1 filter
SMILE: Smooth Motion for Improved Long-Horizon VLA Execution
Jongwoo Park, E-Ro Nguyen, Kanchana Ranasinghe +3
Vision-Language-Action (VLA) models reduce inference cost by executing multiple actions per call, but longer horizons often degrade accuracy because raw chunks contain jitter and o…
LACE: Latent Visual Representation for Cross-Embodiment Learning
Yoo Sung Jang, Kanchana Ranasinghe, Cristina Mata +3
Cross-embodiment learning from human demonstrations is hindered by the visual gap between human and robot embodiments. While self-supervised learning (SSL) backbones encode rich in…
Future Optical Flow Prediction Improves Robot Control & Video Generation
Kanchana Ranasinghe, Honglu Zhou, Yu Fang +7
Future motion representations, such as optical flow, offer immense value for control and generative tasks. However, forecasting generalizable spatially dense motion representations…
IVRA: Improving Visual-Token Relations for Robot Action Policy with Training-Free Hint-Based Guidance
Jongwoo Park, Kanchana Ranasinghe, Jinhyeok Jang +3
Many Vision-Language-Action (VLA) models flatten image patches into a 1D token sequence, weakening the 2D spatial cues needed for precise manipulation. We introduce IVRA, a lightwe…