4 papers
Dual-Stream Diffusion for World-Model Augmented Vision-Language-Action Model
John Won, Kyungmin Lee, Huiwon Jang +2
Augmenting vision-language-action models (VLAs) with world models is promising for robotic policy learning but faces challenges in jointly predicting states and actions due to the…
RLDX-1 Technical Report
Dongyoung Kim, Huiwon Jang, Myungkyu Koo +65
While Vision-Language-Action models (VLAs) have shown remarkable progress toward human-like generalist robotic policies through the versatile intelligence (i.e. broad scene underst…
RoboCurate: Harnessing Diversity with Action-Verified Neural Trajectory for Robot Learning
Seungku Kim, Suhyeok Jang, Byungjun Yoon +3
Synthetic data generated by video generative models has shown promise for robot learning as a scalable pipeline, but it often suffers from inconsistent action quality due to imperf…
CLIP Meets Diffusion: A Synergistic Approach to Anomaly Detection
Byeongchan Lee, John Won, Seunghyun Lee +1
Anomaly detection is a complex problem due to the ambiguity in defining anomalies, the diversity of anomaly types (e.g., local and global defect), and the scarcity of training data…