collaborators

20 papers

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.RO2026

WorldScape Policy 2.0: Empowering Steerable World Action Modeling with Reasoning-Augmented Memory

Haisheng Su, Zongdai Liu, Xin Jin +13

World Action Models (WAMs) offer a promising paradigm for robotic manipulation by jointly modeling visual state transitions and robot actions. However, existing WAMs are constraine…

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.AI2026

DyCon: Dynamic Reasoning Control via Evolving Difficulty Modeling

Tengyao Tu, Yulin Li, Hui-Ling Zhen +6

Recent advances in Large Reasoning Models (LRMs) demonstrate remarkable performance improvements by iteratively reflecting, exploring, and executing complex tasks, yet suffer from…

cs.CV2026

NavOne: One-Step Global Planning for Vision-Language Navigation on Top-Down Maps

Dijia Zhan, Jinyi Li, Chenxi Zheng +4

Existing Vision-Language Navigation (VLN) methods typically adopt an egocentric, step-by-step paradigm, which struggles with error accumulation and limits efficiency. While recent…

cs.RO2026

Dreaming when Necessary: Advancing World Action Models with Adaptive Multi-Modal Reasoning

Yinzhou Tang, Jingbo Xu, Yu Shang +4

World Action Models (WAMs) offer a promising approach to embodied intelligence, yet existing methods rely heavily on video prediction as action priors and lack adaptive multimodal…