2 papers
cs.RO2026
ARS: Agentic Reward System for Robot Learning
Sheng Hu, Weiyi Lu, Lingbing Zeng +5
Progress reward modeling is the problem of estimating how a robot's behavior changes task progress over time. Reliable estimation requires distinguishing meaningful state changes f…
cs.RO2026
DSWAM: A Dual-System World Action Foundation Model for Fine-Grained Robot Manipulation
Jian Zhu, Jianjun Zhang, Taiyi Su +10
World Action Models (WAMs) provide a promising alternative to Vision-Language-Action (VLA) policies by using video-based world modeling as dense supervision for robot action learni…