1 citations · 2 across the 6 of their papers we have counts for
9 papers
LIVE: Long-horizon Interactive Video World Modeling
Junchao Huang, Ziyang Ye, Xinting Hu +5
Autoregressive video world models predict future visual observations conditioned on actions. While effective over short horizons, these models often struggle with long-horizon gene…
Reinforcement Learning with Inverse Rewards for World Model Post-training
Yang Ye, Tianyu He, Shuo Yang +1
World models simulate dynamic environments, enabling agents to interact with diverse input modalities. Although recent advances have improved the visual quality and temporal consis…
Playing with Transformer at 30+ FPS via Next-Frame Diffusion
Xinle Cheng, Tianyu He, Jiayi Xu +3
Autoregressive video models offer distinct advantages over bidirectional diffusion models in creating interactive video content and supporting streaming applications with arbitrary…
MineWorld: a Real-Time and Open-Source Interactive World Model on Minecraft
Junliang Guo, Yang Ye, Tianyu He +4
World modeling is a crucial task for enabling intelligent agents to effectively interact with humans and operate in dynamic environments. In this work, we propose MineWorld, a real…
Fast Autoregressive Video Generation with Diagonal Decoding
Yang Ye, Junliang Guo, Haoyu Wu +5
Autoregressive Transformer models have demonstrated impressive performance in video generation, but their sequential token-by-token decoding process poses a major bottleneck, parti…
AR4D: Autoregressive 4D Generation from Monocular Videos
Hanxin Zhu, Tianyu He, Xiqian Yu +3
Recent advancements in generative models have ignited substantial interest in dynamic 3D content creation (\ie, 4D generation). Existing approaches primarily rely on Score Distilla…