Personalized Federated Learning via Gradient Modulation for Heterogeneous Text Summarization

23 April 2023

Papers citing "Personalized Federated Learning via Gradient Modulation for Heterogeneous Text Summarization"

9 / 9 papers shown

Title
Modular Federated Learning Kuo-Yun Liang A. Srinivasan J. C. Andresen FedML 22 7 0 07 Sep 2022
A Fair Federated Learning Framework With Reinforcement Learning Yaqi Sun Shijing Si Jianzong Wang Yuhan Dong Z. Zhu Jing Xiao FedML 9 7 0 26 May 2022
Federated Learning Challenges and Opportunities: An Outlook Jie Ding Eric W. Tramel Anit Kumar Sahu Shuang Wu Salman Avestimehr Tao Zhang FedML 20 53 0 01 Feb 2022
A Secure and Efficient Federated Learning Framework for NLP Jieren Deng Chenghong Wang Xianrui Meng Yijue Wang Ji Li Sheng Lin Shuo Han Fei Miao Sanguthevar Rajasekaran Caiwen Ding FedML 69 22 0 28 Jan 2022
Mitigating Data Scarceness through Data Synthesis, Augmentation and Curriculum for Abstractive Summarization Ahmed Magooda Diane Litman 27 5 0 17 Sep 2021
CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation Yunfan Shao Zhichao Geng Yitao Liu Junqi Dai Hang Yan Fei Yang Li Zhe Hujun Bao Xipeng Qiu MedIm 54 145 0 13 Sep 2021
Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive Summarization Mengyao Cao Yue Dong Jackie C.K. Cheung HILM 170 144 0 30 Aug 2021
FedProto: Federated Prototype Learning across Heterogeneous Clients Yue Tan Guodong Long Lu Liu Tianyi Zhou Qinghua Lu Jing Jiang Chengqi Zhang FedML 141 287 0 01 May 2021
Revisiting Self-Training for Neural Sequence Generation Junxian He Jiatao Gu Jiajun Shen MarcÁurelio Ranzato SSL LRM 236 269 0 30 Sep 2019