Showing cs.ROShow all
2 papers · 1 filter
cs.RO2025
Masked IRL: LLM-Guided Reward Disambiguation from Demonstrations and Language
Minyoung Hwang, Alexandra Forsey-Smerek, Nathaniel Dennler +1
Robots can adapt to user preferences by learning reward functions from demonstrations, but with limited data, reward models often overfit to spurious correlations and fail to gener…
cs.RO2025
Learning Contextually-Adaptive Rewards via Calibrated Features
Alexandra Forsey-Smerek, Julie Shah, Andreea Bobu
A key challenge in reward learning from human input is that desired agent behavior often changes based on context. For example, a robot must adapt to avoid a stove once it becomes…