Qin, Zhen

Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting

Qin, Z., Jagerman, R., Hui, K., Zhuang, H., Wu, J., Yan, L., Shen, J., Liu, T., Liu, J., Metzler, D., et al. (2023) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 16

Exploring Transformer Extrapolation

Qin, Z., Zhong, Y., & Deng, H. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence

Topic ModelingNatural Language Processing Techniques

Cited by 2

Exploring Transformer Extrapolation

Qin, Z., Zhong, Y., & Deng, H. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

HGRN2: Gated Linear RNNs with State Expansion

Qin, Z., Yang, S., Sun, W., Shen, X., Li, D., Sun, W., & Zhong, Y. (2024) · arXiv

Topic ModelingNeural Networks and Applications

Cited by 1

MiniMax-01: Scaling Foundation Models with Lightning Attention

MiniMax, Li, A., Gong, B., Yang, B., Shan, B., Liu, C., Zhu, C., Zhang, C., Guo, C., Chen, D., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Linear Attention Sequence Parallelism

Sun, W., Qin, Z., Li, D., Shen, X., Qiao, Y., & Zhong, Y. (2024) · arXiv

Parallel Computing and Optimization TechniquesTopic Modeling

Cited by 0