Article

ElevateHead: When Action Heads Need One-Time Decisions in Multimodal Imitation Learning

ElevateHead proposes an action head that selects the task execution mode once at a learned decision point and keeps it fixed for the entire episode; users can also set this choice as an input. On held-out Franka Kitchen tasks, 45.2% of its episodes completed all four subtasks, versus 29.3% for BeT (+0.160, 95% CI [+0.129, +0.188]); on held-out block stacking tasks, version 4 was comparable to BeT but did not surpass it.

Part of the event: ElevateHead: An Action Head that Decides Once and Commits

This page provides a summary and source link only.