Xinlei Chen

CoDrive: Cross-Vehicle World-Consistent Video Generation with Precise Trajectory Control for Cooperative Driving

Yu Meng, Baining Zhao, Junta Wu +10

Real-world driving is inherently multi-agent, yet most existing driving world models generate observations from a single ego vehicle. Independently extending them to multiple vehic…

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…

SCOUT: Unlocking Enhanced Spatial Reasoning via Structured Chain-of-Thought and Multi-Objective Process Reward

Zile Zhou, Huining Yuan, Weichen Zhang +2

Existing Vision-Language Models (VLMs) exhibits a critical bottleneck in robust spatial reasoning. Recent reinforcement learning (RL) methods aim to close this gap with verifiable…

ActiveFly-Bench: Aligning Embodied Question Answering with Vision-Language-Action for Aerial Embodied Perception

Weichen Zhang, Shiquan Yu, Yinan Zhu +9

We introduce ActiveFly-Bench, the first benchmark to bridge cyberspace reasoning and physical-world interaction for UAV embodied perception. The benchmark decomposes active percept…

Uncertainty-Aware World Model for Aerial Image-Goal Navigation

Deyi Zhu, Haoyu Fan, Yinan Zhu +4

Aerial image-goal navigation requires an unmanned aerial vehicle (UAV) to reach a target location specified by a goal image. Existing world-model-based methods rank candidate traje…

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…

TetherCache: Stabilizing Autoregressive Long-Form Video Generation with Gated Recall and Trusted Alignment

Yu Meng, Xiangyang Luo, Letian Li +5

Autoregressive video diffusion models provide a natural formulation for streaming and variable-length video generation by conditioning newly generated frames on previously generate…

WorldFly: A World-Model-Based Vision-Language-Action Model for UAV Navigation

Shengtao Zheng, Kai Li, Weichen Zhang +5

End-to-end Vision-Language-Action (VLA) models have shown promise in UAV navigation. However, existing approaches typically rely on historical observations to directly predict acti…

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…

iWorld-Bench: A Benchmark for Interactive World Models with a Unified Action Generation Framework

Jianjie Fang, Yingshan Lei, Qin Wan +8

Achieving Artificial General Intelligence (AGI) requires agents that learn and interact adaptively, with interactive world models providing scalable environments for perception, re…

How Far Are Large Multimodal Models from Human-Level Spatial Action? A Benchmark for Goal-Oriented Embodied Navigation in Urban Airspace

Baining Zhao, Ziyou Wang, Jianjie Fang +8

Large multimodal models (LMMs) show strong visual-linguistic reasoning but their capacity for spatial decision-making and action remains unclear. In this work, we investigate wheth…

WorldMAP: Bootstrapping Vision-Language Navigation Trajectory Prediction with Generative World Models

Hongjin Chen, Shangyun Jiang, Tonghua Su +4

Vision-language models (VLMs) and generative world models are opening new opportunities for embodied navigation. VLMs are increasingly used as direct planners or trajectory predict…