1 citations · 1 across the 3 of their papers we have counts for
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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…
Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling
Haoyu Wu, Diankun Wu, Tianyu He +4
Videos inherently represent 2D projections of a dynamic 3D world. However, our analysis suggests that video diffusion models trained solely on raw video data often fail to capture…
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…
A Hybrid Generative and Discriminative PointNet on Unordered Point Sets
Yang Ye, Shihao Ji
As point cloud provides a natural and flexible representation usable in myriad applications (e.g., robotics and self-driving cars), the ability to synthesize point clouds for analy…