2 citations · 3 across the 7 of their papers we have counts for
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cs.RO2026
WAVE-0: Bridging VLA Policies and WAMs with Lightweight Latent Future Prediction
Haomin Wang, Anqiong Ji, Ke Wang +4
Vision-language-action (VLA) policies excel at generalist robotic manipulation but generate actions without explicitly modeling their environmental consequences. World action model…
cs.CV2026
The Blind Spot of Adaptation: Quantifying and Mitigating Forgetting in Fine-tuned Driving Models
Runhao Mao, Hanshi Wang, Yixiang Yang +3
The integration of Vision-Language Models (VLMs) into autonomous driving promises to solve long-tail scenarios, but this paradigm faces the critical and unaddressed challenge of ca…
cs.CV2026
FlowAD: Ego-Scene Interactive Modeling for Autonomous Driving
Mingzhe Guo, Yixiang Yang, Chuanrong Han +4
Effective environment modeling is the foundation for autonomous driving, underpinning tasks from perception to planning. However, current paradigms often inadequately consider the…