Recent developments in foundation models, like Large Language Models (LLMs) and Vision-
Language Models (VLMs), trained on extensive data, facilitate flexible application across …

Conventional wisdom holds that autoregressive models for image generation are typically
accompanied by vector-quantized tokens. We observe that while a discrete-valued space …

World models empower model-based agents to interactively explore, reason, and plan
within imagined environments for real-world decision-making. However, the high demand …

Diffusion policies are conditional diffusion models that learn robot action distributions
conditioned on the robot and environment state. They have recently shown to outperform …

Open-vocabulary generalization requires robotic systems to perform tasks involving complex
and diverse environments and task goals. While the recent advances in vision language …

The field of robotics has made significant advances towards generalist robot manipulation
policies. However, real-world evaluation of such policies is not scalable and faces …

Open-sourced, user-friendly tools form the bedrock of scientific advancement across
disciplines. The widespread adoption of data-driven learning has led to remarkable …