9 papers
GUICrafter: Weakly-Supervised GUI Agent Leveraging Massive Unannotated Screenshots
Sunqi Fan, Lingshan Chen, Runqi Yin +4
Data, as the fundamental substrate of modern intelligence, has greatly driven the development of current foundation models. Naturally, researchers aim to extend this paradigm to th…
TopoCap: Learning Topology-Agnostic Motion Priors for Monocular Video-to-Animation
Cheng-Feng Pu, Jia-Peng Zhang, Meng-Hao Guo +2
The explosion of generative 3D assets has created a massive demand for animation, yet current motion capture methods remain brittle, restricted to species-specific templates (e.g.,…
Pixal3D: Pixel-Aligned 3D Generation from Images
Dong-Yang Li, Wang Zhao, Yuxin Chen +5
Recent advances in 3D generative models have rapidly improved image-to-3D synthesis quality, enabling higher-resolution geometry and more realistic appearance. Yet fidelity, which…
Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts
Yuxuan Han, Meng-Hao Guo, Zhengning Liu +2
Optimizing GPU kernels manually is a challenging and time-consuming task. With the rapid development of LLMs, automated GPU kernel optimization is gradually becoming a tangible rea…
Improving Variable-Length Generation in Diffusion Language Models via Length Regularization
Zicong Cheng, Ruixuan Jia, Jia Li +3
Diffusion Large Language Models (DLLMs) are inherently ill-suited for variable-length generation, as their inference is defined on a fixed-length canvas and implicitly assumes a kn…
Skin Tokens: A Learned Compact Representation for Unified Autoregressive Rigging
Jia-peng Zhang, Cheng-Feng Pu, Meng-Hao Guo +2
The rapid proliferation of generative 3D models has created a critical bottleneck in animation pipelines: rigging. Existing automated methods are fundamentally limited by their app…