Sun, Yuxuan

MMMU: A Massive Multi-Discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI

Yue, X., Ni, Y., Zheng, T., Zhang, K., Liu, R., Zhang, G., Stevens, S., Jiang, D., Ren, W., Sun, Y., et al. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 429

MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark

Yue, X., Zheng, T., Ni, Y., Wang, Y., Zhang, K., Tong, S., Sun, Y., Yu, B., Zhang, G., Sun, H., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 4

AAAR-1.0: Assessing AI's Potential to Assist Research

Lou, R., Xu, H., Wang, S., Du, J., Kamoi, R., Lu, X., Xie, J., Sun, Y., Zhang, Y., Ahn, J. J., et al. (2024) · arXiv

Topic ModelingArtificial Intelligence Applications

Cited by 3

Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models

Liu, R., Sun, Y., Zhang, M., Bai, H., Yu, X., Yu, T., Yuan, C., & Hou, L. (2025) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 0