Zhang, Qi

Time-Series Anomaly Detection Service at Microsoft

Ren, H., Xu, B., Wang, Y., Yi, C., Huang, C., Kou, X., Xing, T., Yang, M., Tong, J., & Zhang, Q. (2019) · Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Anomaly Detection Techniques and ApplicationsSoftware System Performance and Reliability

Cited by 623

BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction

Li, Y., Gong, R., Tan, X., Yang, Y., Hu, P., Zhang, Q., Yu, F., Wang, W., & Gu, S. (2021) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 190

SciER: An Entity and Relation Extraction Dataset for Datasets, Methods, and Tasks in Scientific Documents

Zhang, Q., Chen, Z., Pan, H., Caragea, C., Latecki, L. J., & Dragut, E. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Topic ModelingBiomedical Text Mining and Ontologies

Cited by 21

LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration

Zhao, J., Zu, C., Xu, H., Lu, Y., He, W., Ding, Y., Gui, T., Zhang, Q., & Huang, X. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

Cheng, D., Huang, S., Bi, J., Zhan, Y., Liu, J., Wang, Y., Sun, H., Wei, F., Deng, D., & Zhang, Q. (2023) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 2