Which data is best for training few-shot imitation policies for robot manipulation? Some think it’s the data that looks similar, or has similar motion, or comes with related language labels. They are all right AND wrong: depending on the task, sometimes this similarity helps but

Intelligent humanoids should have the ability to quickly adapt to new tasks by observing humans Why is such adaptability important? 🌍 Real-world diversity is hard to fully capture in advance 🧠 Adaptability is central to natural intelligence We present MimicDroid 👇 🌐

Ever wondered which data from large datasets (like OXE) actually helps when training/tuning a policy for specific tasks? We present DataMIL, a framework for measuring how each training sample influences policy performance, hence enabling effective data selection 🧵

🚀 Despite efforts to scale up Behavior Cloning for Robots, large-scale BC has yet to live up to its promise. How can we break through the performance plateau? Introducing 🔥FLaRe: fine-tuning large-scale robot policies with Reinforcement Learning. robot-flare.github.io 🧵