works on

From the 1 of 21 linked papers with an AI index.

activity
20242026
collaborators

21 papers

cs.RO2026

BrainWAM: Action-Space Coordination of Semantic Priors and Predictive Dynamics for Autonomous Driving

Bing Zhan, Shuyao Shang, Jiahao Gu +8

Autonomous driving requires planning under both semantic constraints and predictive dynamics. Existing end-to-end driving approaches, however, typically emphasize only one side of…

cs.CV2026

WorldExam: Benchmarking World Models from Apparent Appearance to Inherent Reactivity

Yuxue Yang, Shuyao Shang, Jiahe Wang +13

Controllable video generation models are increasingly being developed as world models. Accordingly, evaluating them in this role extends beyond the apparent appearance of generated…

cs.CV2026

PhiZero: A World Model Built Around Physical Language

Shuyao Shang, Yuqi Wang, Ruopeng Gao +4

PhiZero is a physical world model that learns a compact discrete "physical language" from videos to predict future world states as language sequences before rendering them into rea…

cs.RO2026

Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models

Yifu Yuan, Yaoting Huang, Xianze Yao +20

We introduce Embodied-R1.5, a unified Embodied Foundation Model (EFM) that integrates comprehensive embodied reasoning capabilities, spanning embodied cognition, task planning, cor…

cs.RO2026

World Pilot: Steering Vision-Language-Action Models with World-Action Priors

Zefu Lin, Rongxu Cui, Junjia Xu +4

Vision-Language-Action (VLA) models inherit semantic grounding from large-scale pretraining and perform competently across in-distribution manipulation tasks. This grounding, howev…

cs.CV2026

DynVLA: Learning World Dynamics for Action Reasoning in Autonomous Driving

Shuyao Shang, Bing Zhan, Yunfei Yan +9

We propose DynVLA, a driving VLA model that introduces a new CoT paradigm termed Dynamics CoT. DynVLA forecasts compact world dynamics before action generation, enabling more infor…