Wang, Jiaqi

MMBench: Is Your Multi-modal Model an All-Around Player?

Liu, Y., Duan, H., Zhang, Y., Li, B., Zhang, S., Zhao, W., Yuan, Y., Wang, J., He, C., Liu, Z., et al. (2025) · Lecture Notes in Computer Science

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 668

MMBench: Is Your Multi-modal Model an All-around Player?

Liu, Y., Duan, H., Zhang, Y., Li, B., Zhang, S., Zhao, W., Yuan, Y., Wang, J., He, C., Liu, Z., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 487

A Comprehensive Review of Multimodal Large Language Models: Performance and Challenges Across Different Tasks

Wang, J., Jiang, H., Liu, Y., Ma, C., Zhang, X., Pan, Y., Liu, M., Gu, P., Xia, S., Chen, L., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 21

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