4 papers
Enhancing Joint Human-AI Inference in Robot Missions: A Confidence-Based Approach
Duc-An Nguyen, Clara Colombatto, Steve Fleming +3
Joint human-AI inference holds immense potential to improve outcomes in human-supervised robot missions. Current day missions are generally in the AI-assisted setting, where the hu…
LUMOS: Language-Conditioned Imitation Learning with World Models
Iman Nematollahi, Branton DeMoss, Akshay L Chandra +3
We introduce LUMOS, a language-conditioned multi-task imitation learning framework for robotics. LUMOS learns skills by practicing them over many long-horizon rollouts in the laten…
Joint Decision-Making in Robot Teleoperation: When are Two Heads Better Than One?
Duc-An Nguyen, Raunak Bhattacharyya, Clara Colombatto +3
Operators working with robots in safety-critical domains have to make decisions under uncertainty, which remains a challenging problem for a single human operator. An open question…
The Complexity Dynamics of Grokking
Branton DeMoss, Silvia Sapora, Jakob Foerster +2
We demonstrate the existence of a complexity phase transition in neural networks by studying the grokking phenomenon, where networks suddenly transition from memorization to genera…