2 papers
eess.SY2026
Policy-Level Recursive Self-Improvement for Embodied AI with a Criticality World Model
Linxuan He, Yuying Tian, Lingxiang Fan +5
Despite advances in policy pretraining, embodied AI systems can plateau during task-specific fine-tuning as uniform scenario collection encounters fewer of the remaining failures.…
cs.RO2026
DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models
Haoyuan Ji, Lingxiang Fan, Shang Su +4
World-Action Models (WAMs) augment robot policies with future visual prediction, but it remains unclear what the visual modality should learn for control. While photorealistic futu…