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.