CORTEXA
← Browse

Haiyang Sun

2 papers indexed

arxivcs.ROcs.AI2026-06-29

Pondering the Way: Spatial-perceiving World Action Model for Embodied Navigation

Hong Chen, Daqi Liu, Zehan Zhang, Haiguang Wang, Tianhao Lu, Longfei Yan, et al.

Existing world model-based planners for visual navigation typically follow a verification-centric paradigm, decoupling goal intent from trajectory synthesis. This approach suffers from candidate dependence, heavy computational overhead, and inconsistencies between sampled actions…

View free PDFSource page
arxivcs.CV2026-06-25

ReWorld: Learning Better Representations for World Action Models

Tianze Xia, Lijun Zhou, Kaixin Xiong, Jingfeng Yao, Yu Zhu, Zhenxin Zhu, et al.

World Action Models (WAMs) model future environment evolution under action conditioning, offering a scalable paradigm for autonomous driving. However, existing approaches focus largely on model architecture design, and how a WAM can efficiently learn better world representations…

View free PDFSource page