collaborators

15 papers

cs.AI2026

IMPACT: Attention Is the Interaction Map for Scalable Interaction-Aware World Model Training

Rongze Tang, Jianjie Fang, Zhaolu Wang +8

World models have made remarkable progress in action-conditioned future prediction for embodied agents, yet still struggle to model physically plausible interactions. Existing appr…

cs.AI2026

CAER: Causal Action Effect Reweighting for World Model Training

Jianjie Fang, Xvyuan Liu, Ziyou Wang +9

World models are becoming core infrastructure for embodied intelligence, with action-conditioned video generation providing controllable predictions of how scenes evolve after agen…

cs.RO2026

UniETP: Unifying Environments for Generalizable Embodied Task Planning

Peiran Xu, Jiaqi Zheng, Ziyou Wang +1

This paper focuses on the problem of Embodied Task Planning, where an agent is required to execute a sequence of atomic actions within an interactive environment to complete a user…

cs.RO2026

Worldscape-MoE: A Unified Mixture-of-Experts World Model for Scalable Heterogeneous Action Control

Jianjie Fang, Yongyan Xu, Ziyou Wang +13

World models are rapidly becoming a core infrastructure for embodied intelligence and interactive agents: they provide controllable simulators in which agents can perceive, act, fo…

cs.RO2026

WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform

Yu Shang, Yinzhou Tang, Yiding Ma +22

World models have emerged as a central paradigm for embodied intelligence, enabling agents to predict action-conditioned future and reason about environmental dynamics. However, ex…

cs.RO2026

WorldVLN: Autoregressive World Action Model for Aerial Vision-Language Navigation

Baining Zhao, Jiacheng Xu, Weicheng Feng +13

Aerial vision-language navigation (VLN) requires agents to follow natural-language instructions through closed-loop perception and action in 3D environments. We argue that aerial V…