collaborators

11 papers

cs.AI2026

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…

cs.CV2026

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.,…

cs.CV2026

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…

cs.CV2026

OSCBench: Benchmarking Object State Change in Text-to-Video Generation

Xianjing Han, Bin Zhu, Shiqi Hu +4

Text-to-video (T2V) generation models have made rapid progress in producing visually high-quality and temporally coherent videos. However, existing benchmarks primarily focus on pe…

cs.CV2026

Bee: A High-Quality Corpus and Full-Stack Suite to Unlock Advanced Fully Open MLLMs

Yi Zhang, Bolin Ni, Xin-Sheng Chen +7

Fully open multimodal large language models (MLLMs) currently lag behind proprietary counterparts, primarily due to a significant gap in data quality for supervised fine-tuning (SF…

cs.LG2026

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…