5 papers · 1 filter
LeapBot-JAC: Joint Action Chains for World Action Models
Chenhao Zhu, Baibing Liu, Pei Liu +5
Action-chunking policies predict future controls but execute only a prefix before replanning. How should a fixed action-token budget be organized to support execution? We propose L…
ReWAM: Reciprocal World Action Models for Interactive Autonomous Driving
Benshan Ma, Pei Liu, Ruiguo Zhong +4
In interactive scenarios, an autonomous driving system is required to generate ego actions under the influence of other agents' behaviors. Existing World Action Models (WAMs) typic…
DA-WAM: Decision-Aligned Future Latents for Driving World Models
Ruiguo Zhong, Benshan Ma, Xiaolong Chen +5
World models for autonomous driving should anticipate the consequences that matter for driving decisions rather than reconstruct every detail of future scenes. However, predictive…
LeapBot-WA: World-Anchor Action Models via Predictive Latent Alignments
Pei Liu, Nan Zheng, Lang Zhang +8
World Action Models (WAMs) have emerged as a powerful paradigm for embodied intelligence, yet the prevailing reliance on pixel-level video generation creates a fundamental bottlene…
Rethinking Closed-loop Planning Framework for Imitation-based Model Integrating Prediction and Planning
Jiayu Guo, Mingyue Feng, Pengfei Zhu +2
In recent years, the integration of prediction and planning through neural networks has received substantial attention. Despite extensive studies on it, there is a noticeable gap i…