The author has released Calibra, a tool designed to identify poor demonstrations in robotics imitation learning datasets before they consume GPU resources.

  • The project focuses on dataset observability to filter out bad data.
  • It implements coreset selection to prioritize the most significant episodes for training.
  • The code is available via a GitHub repository linked in the announcement.

The author invites feedback and advice from the community regarding the tool's functionality.