no code implementations • 20 May 2024 • Liuzhi Zhou, Yu He, Kun Zhai, Xiang Liu, Sen Liu, Xingjun Ma, Guangnan Ye, Yu-Gang Jiang, Hongfeng Chai
This comparative analysis revealed that due to the limited information contained within client models from other clients during the initial stages of federated learning, more substantial constraints need to be imposed on the parameters of the adaptive algorithm.
1 code implementation • 3 Nov 2023 • YuHang Zhou, He Yu, Siyu Tian, Dan Chen, Liuzhi Zhou, Xinlin Yu, Chuanjun Ji, Sen Liu, Guangnan Ye, Hongfeng Chai
While current NL2SQL tasks constructed using Foundation Models have achieved commendable results, their direct application to Natural Language to Graph Query Language (NL2GQL) tasks poses challenges due to the significant differences between GQL and SQL expressions, as well as the numerous types of GQL.