4 papers
DA-WAM: Decision-Aligned Future Latents for Driving World Models
Ruiguo Zhong, Benshan Ma, Xiaolong Chen +5
Anticipating how scenes evolve under ego actions is fundamental to safe autonomous driving, yet the full potential of world models for decision-making remains unrealized. The criti…
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…
Decoupling Scene Perception and Ego Status: A Multi-Context Fusion Approach for Enhanced Generalization in End-to-End Autonomous Driving
Jiacheng Tang, Mingyue Feng, Jiachao Liu +2
Modular design of planning-oriented autonomous driving has markedly advanced end-to-end systems. However, existing architectures remain constrained by an over-reliance on ego statu…
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…