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cs.CV2026

WildWorld: A Large-Scale Dataset for Dynamic World Modeling with Actions and Explicit State toward Generative ARPG

Zhen Li, Zian Meng, Shuwei Shi +5

Dynamical systems theory and reinforcement learning view world evolution as latent-state dynamics driven by actions, with visual observations providing partial information about th…

cs.CV2025

Yume-1.5: A Text-Controlled Interactive World Generation Model

Xiaofeng Mao, Zhen Li, Chuanhao Li +6

Recent approaches have demonstrated the promise of using diffusion models to generate interactive and explorable worlds. However, most of these methods face critical challenges suc…

cs.CV2025

Yume: An Interactive World Generation Model

Xiaofeng Mao, Shaoheng Lin, Zhen Li +7

Yume aims to use images, text, or videos to create an interactive, realistic, and dynamic world, which allows exploration and control using peripheral devices or neural signals. In…

cs.CV2025

Sekai: A Video Dataset towards World Exploration

Zhen Li, Chuanhao Li, Xiaofeng Mao +17

Video generation techniques have made remarkable progress, promising to be the foundation of interactive world exploration. However, existing video generation datasets are not well…

cs.CV2025

MDK12-Bench: A Multi-Discipline Benchmark for Evaluating Reasoning in Multimodal Large Language Models

Pengfei Zhou, Fanrui Zhang, Xiaopeng Peng +17

Multimodal reasoning, which integrates language and visual cues into problem solving and decision making, is a fundamental aspect of human intelligence and a crucial step toward ar…