Zhang, Shanghang

Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting

Zhou, H., Zhang, S., Peng, J., Zhang, S., Li, J., Xiong, H., & Zhang, W. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence

Time Series Analysis and ForecastingEnergy Load and Power Forecasting

Cited by 7,752

ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate

Chan, C.-M., Chen, W., Su, Y., Yu, J., Xue, W., Zhang, S., Fu, J., & Liu, Z. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 725

NoisyQuant: Noisy Bias-Enhanced Post-Training Activation Quantization for Vision Transformers

Liu, Y., Yang, H., Dong, Z., Keutzer, K., Du, L., & Zhang, S. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 60

Training-free Regional Prompting for Diffusion Transformers

Chen, A., Xu, J., Zheng, W., Dai, G., Wang, Y., Zhang, R., Wang, H., & Zhang, S. (2024) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 0

FastDriveVLA: Efficient End-to-End Driving via Plug-and-Play Reconstruction-based Token Pruning

Cao, J., Zhang, Q., Jia, P., Zhao, X., Lan, B., Zhang, X., Li, Z., Wei, X., Chen, S., Li, L., et al. (2025) · arXiv

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 0