Andrea M. Salcedo-Vázquez

Robust Instant Policy: Student’s-t-Based Trajectory Aggregation for Reliable In-Context Imitation Learning in Robot Manipulation

Imitation learning (IL) enables robots to acquire autonomous skills from human demonstrations. Recent in-context IL (ICIL) methods leverage off-the-shelf large language models (LLMs) as instant policies that infer task context and generate executable trajectories from only a few demonstrations, without retraining model...