🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

Reward models that help real robots learn new tasks—no new demos needed! ReWiND uses language-guided rewards to train bimanual arms on OOD tasks in 1 hour! Offline-to-online, lang-conditioned, visual RL on action-chunked transformers. 🧵

How can non-experts quickly teach robots a variety of tasks? Introducing HAND ✋, a simple, time-efficient method of training robots! Using just a **single hand demo**, HAND learns manipulation tasks in under **4 minutes**! 🧵

With just a single 2D hand path, we can retrieve relevant trajectories from a task-agnostic play dataset to help robots learn manipulation tasks! Excited to share my first first-author project!

Check out our latest work on robot learning from human hand demonstrations! HAND ✋ can learn new manipulation policies in under 4 minutes from a single hand demo! Huge shoutout to my collaborators and Matthew Hong who will be applying to PhD programs this year!

Just a small reminder that our workshop is happening tomorrow, and we have an amazing line of speakers! Make sure to check out the workshop website for the schedule. 🤖

So you’ve trained your favorite diffusion/flow based policy, but it’s just not good enough 0-shot. Worry not, in our new work DSRL - we show how to *steer* pre-trained diffusion policies with off-policy RL, improving behavior efficiently enough for direct training in the real