My interests span computer vision and computer graphics. Though no longer actively publishing, I keep up with research trends — with a particular focus on Efficient AI in the era of large models.
Songwei Liu, Chao Zeng, Chenqian Yan, Xurui Peng, Xing Wang, Fangmin Chen, Xing Mei. Error Propagation Mechanisms and Compensation Strategies for Quantized Diffusion Models. In ICML 2026. (oral)
Chao Zeng, Songwei Liu, Yusheng Xie, Hong Liu, Xiaojian Wang, Miao Wei, Shu Yang, Fangmin Chen, Xing Mei. ABQ-LLM: Arbitrary-Bit Quantized Inference Acceleration for Large Language Models. In AAAI 2025. [GitHub]
Han Yan, Celong Liu, Chao Ma, Xing Mei. PlenVDB: Memory Efficient VDB-Based Radiance Fields for Fast Training and Rendering. In CVPR 2023. [project page]
Huaiyu Li, Weiming Dong, Xing Mei, Chongyang Ma, Feiyue Huang, Bao-Gang Hu. LGM-Net: Learning to Generate Matching Networks for Few-Shot Learning. In ICML 2019. [code]