UPS framework uses conformal prediction to calibrate VLM verifiers for choosing between high-confidence action execution, natural language task queries, or policy interventions, then applies residual learning from interventions to continually improve the base policy with minimal feedback.
Mastering diverse domains through world models.Nature
2 Pith papers cite this work. Polarity classification is still indexing.
fields
cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
PIEGraph augments a spring-mass particle model with an equivariant GNN and novel action representation to predict accurate object dynamics for robotic manipulation from few interactions.
citing papers explorer
-
When to Act, Ask, or Learn: Uncertainty-Aware Policy Steering
UPS framework uses conformal prediction to calibrate VLM verifiers for choosing between high-confidence action execution, natural language task queries, or policy interventions, then applies residual learning from interventions to continually improve the base policy with minimal feedback.
-
Learning Equivariant Neural-Augmented Object Dynamics From Few Interactions
PIEGraph augments a spring-mass particle model with an equivariant GNN and novel action representation to predict accurate object dynamics for robotic manipulation from few interactions.