Duan, Haodong

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

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