13 papers
Language as a Sensor: Calibrated Spatial Belief Estimation in 3D Scenes from Natural Language
Aryan Naveen, Jason Xinyu Liu, Luca Carlone +1
Robots deployed in human-centric environments routinely receive natural-language descriptions of spatial information ("I left my backpack on the table") that reference parts of the…
QuickLAP: Quick Language-Action Preference Learning for Semi-Autonomous Agents
Jordan Abi Nader, David Lee, Nathaniel Dennler +1
Robots must learn from both what people do and what they say, but either modality alone is often incomplete: physical corrections are grounded but ambiguous in intent, while langua…
Human-Guided Harm Recovery for Computer Use Agents
Christy Li, Sky CH-Wang, Andi Peng +1
As LM agents gain the ability to execute actions on real computer systems, we need ways to not only prevent harmful actions at scale but also effectively remediate harm when preven…
Robots That Know What to Ask: Recovering Misaligned Rewards through Targeted Explanations
Helena Merker, Nick Walker, Andreea Bobu
Learning reward functions from demonstrations assumes that demonstrations provide adequate supervision over all features -- or task-relevant aspects of behavior. In practice, demon…
Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons
Anthony Liang, Yigit Korkmaz, Jiahui Zhang +14
General-purpose robot reward models are typically trained to predict absolute task progress from expert demonstrations, providing only local, frame-level supervision. While effecti…
Flexible Agent Alignment with Goal Inference from Open-Ended Dialog
Rachel Ma, Jingyi Qu, Andreea Bobu +1
We introduce Open-Universe Assistance Games (OU-AGs), a formal framework extending assistance games to LLM-based agents. Effective assistance requires reasoning over human preferen…