Ren, Weiming

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

MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

Wang, Y., Ma, X., Zhang, G., Ni, Y., Chandra, A., Guo, S., Ren, W., Arulraj, A., He, X., Jiang, Z., et al. (2024) · Advances in Neural Information Processing Systems 37

Topic ModelingNatural Language Processing Techniques

Cited by 131

MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

Wang, Y., Ma, X., Zhang, G., Ni, Y., Chandra, A., Guo, S., Ren, W., Arulraj, A., He, X., Jiang, Z., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 131

ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation

Ren, W., Yang, H., Zhang, G., Wei, C., Du, X., Huang, W., & Chen, W. (2024) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 4