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cs.CV2026

Pathwise Test-Time Correction for Autoregressive Long Video Generation

Xunzhi Xiang, Zixuan Duan, Guiyu Zhang +7

Distilled autoregressive diffusion models facilitate real-time short video synthesis but suffer from severe error accumulation during long-sequence generation. While existing Test-…

cs.CV2026

Elastic Diffusion Transformer

Jiangshan Wang, Zeqiang Lai, Jiarui Chen +5

Diffusion Transformers (DiT) have demonstrated remarkable generative capabilities but remain highly computationally expensive. Previous acceleration methods, such as pruning and di…

cs.CV2026

WorldCompass: Reinforcement Learning for Long-Horizon World Models

Zehan Wang, Tengfei Wang, Haiyu Zhang +9

This work presents WorldCompass, a novel Reinforcement Learning (RL) post-training framework for the long-horizon, interactive video-based world models, enabling them to explore th…

cs.CV2025

MoCA: Mixture-of-Components Attention for Scalable Compositional 3D Generation

Zhiqi Li, Wenhuan Li, Tengfei Wang +8

Compositionality is critical for 3D object and scene generation, but existing part-aware 3D generation methods suffer from poor scalability due to quadratic global attention costs…

cs.CV2025

FlashWorld: High-quality 3D Scene Generation within Seconds

Xinyang Li, Tengfei Wang, Zixiao Gu +3

We propose FlashWorld, a generative model that produces 3D scenes from a single image or text prompt in seconds, 10~100 faster than previous works while possessing superior…

cs.CV2025

VoxHammer: Training-Free Precise and Coherent 3D Editing in Native 3D Space

Lin Li, Zehuan Huang, Haoran Feng +4

3D local editing of specified regions is crucial for game industry and robot interaction. Recent methods typically edit rendered multi-view images and then reconstruct 3D models, b…