RoboPapers
Starting to listen to these podcasts hosted by Chris Paxton. I think if you just spend the time to read those papers, then you can come up with some brilliant ideas.
Episode 1: SAM2Act
- Why not just increase the context window size so that the robot remembers more things, as opposed to coming up with new architecture? Author talks about compounding error, I don’t understand what he refers to that
Episode 2: Robot Utility Models General Policies for ZeroShot Deployment in New Environments
Episode 4: Vision Language Models are InContext Value Learners by Jason
Episode 15: Navigation World Models
Episode 17: EgoZero Robot Learning from Smart Glasses
Episode 18: HuB Learning Extreme Humanoid Balance
- Chris paxton: “I think these were some of the coolest humanoid balancing videos i’ve seen”
Episode 19: Learning to Drive from a World Model
Episode 20: VideoMimic
Episode 22: DexWild
- sheesh my boy jason liu here