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) typically model other agents as components of the world model rather than as decision-makers that fundamentally shape the action of the ego agent,...
Ben-Shan Ma, Pei Liu, Rui-Guo Zhong et al.· 0 citations
This work introduces a query-adaptive neuro-symbolic reasoning framework that explicitly allocates computation according to the nature of the query and shifts the role of the LLM from a universal reasoning engine to a targeted semantic reasoner, while allowing deterministic computation to be handled exactly and efficie...
Yi-Yao Wang, Pei Liu, Fang Liu et al.· 0 citations
LaPla is introduced, a unified Vision-Language-Action framework featuring latent-aligned planning to seamlessly ground semantic understanding in precise motion execution to bridge the modality gap between high-dimensional semantics and the raw action space.
Ruo-Yu Yao, Yu-Sen Xie, Qing-Zhao Liu et al.· 0 citations
DA-WAM is proposed, a framework that unifies predictive representation learning, action-conditioned future modeling, and trajectory scoring under a single decision-making objective and demonstrates state-of-the-art performance on NAVSIM-v1 and NAVSIM-v2.
Rui-Guo Zhong, Ben-Shan Ma, Xiao-Long Chen et al.· 4 citations
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