Zang, Yuhang

Are We on the Right Way for Evaluating Large Vision-Language Models?

Chen, L., Li, J., Dong, X., Zhang, P., Zang, Y., Chen, Z., Duan, H., Wang, J., Qiao, Y., Lin, D., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 108

VLMEvalKit: An Open-Source ToolKit for Evaluating Large Multi-Modality Models

Duan, H., Yang, J., Qiao, Y., Fang, X., Chen, L., Liu, Y., Dong, X., Zang, Y., Zhang, P., Wang, J., et al. (2024) · Proceedings of the 32nd ACM International Conference on Multimedia

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 95

InternLM2 Technical Report

Cai, Z., Cao, M., Chen, H., Chen, K., Chen, K., Chen, X., Chen, X., Chen, Z., Chen, Z., Chu, P., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 30

SAM2LONG: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree

Ding, S., Qian, R., Dong, X., Zhang, P., Zang, Y., Cao, Y., Guo, Y., Lin, D., & Wang, J. (2025) · 2025 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 19

SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree

Ding, S., Qian, R., Dong, X., Zhang, P., Zang, Y., Cao, Y., Guo, Y., Lin, D., & Wang, J. (2024) · arXiv

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 19

MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing

Niu, J., Liu, Z., Gu, Z., Wang, B., Ouyang, L., Zhao, Z., Chu, T., He, T., Wu, F., Zhang, Q., et al. (2025) · arXiv

Handwritten Text Recognition TechniquesAdvanced Neural Network Applications

Cited by 3

Visual-ERM: Reward Modeling for Visual Equivalence

Liu, Z., Ding, S., Fang, X., Dai, X., Yang, P., Liang, J., Wang, J., Chen, K., Lin, D., & Zang, Y. (2026) · arXiv

Multimodal Machine Learning ApplicationsSoftware Engineering Research

Cited by 0