Zhou, Pan

A Survey of Model Compression and Acceleration for Deep Neural Networks

Cheng, Y., Wang, D., Zhou, P., & Zhang, T. (2017) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 857

Model Compression and Acceleration for Deep Neural Networks: The Principles, Progress, and Challenges

Cheng, Y., Wang, D., Zhou, P., & Zhang, T. (2018) · IEEE Signal Processing Magazine

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 817

InPrivate Digging: Enabling Tree-based Distributed Data Mining with Differential Privacy

Zhao, L., Ni, L., Hu, S., Chen, Y., Zhou, P., Xiao, F., & Wu, L. (2018) · IEEE INFOCOM 2018 - IEEE Conference on Computer Communications

Privacy-Preserving Technologies in DataCryptography and Data Security

Cited by 108

Masked Diffusion Transformer is a Strong Image Synthesizer

Gao, S., Zhou, P., Cheng, M.-M., & Yan, S. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 91

Can LLMs Correct Themselves? A Benchmark of Self-Correction in LLMs

Tie, G., Yuan, Z., Zhao, Z., Hu, C., Gu, T., Zhang, R., Zhang, S., Wu, J., Tu, X., Jin, M., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 16

MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark

Chen, D., Chen, R., Zhang, S., Liu, Y., Wang, Y., Zhou, H., Zhang, Q., Wan, Y., Zhou, P., & Sun, L. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 6