FedGSM: Efficient Federated Learning for LEO Constellations with Gradient Staleness Mitigation

no code implementations • 17 Apr 2023 • Lingling Wu, Jingjing Zhang

Recent advancements in space technology have equipped low Earth Orbit (LEO) satellites with the capability to perform complex functions and run AI applications.

Federated Learning

A Simple Hash-Based Early Exiting Approach For Language Understanding and Generation

1 code implementation • Findings (ACL) 2022 • Tianxiang Sun, Xiangyang Liu, Wei Zhu, Zhichao Geng, Lingling Wu, Yilong He, Yuan Ni, Guotong Xie, Xuanjing Huang, Xipeng Qiu

Previous works usually adopt heuristic metrics such as the entropy of internal outputs to measure instance difficulty, which suffers from generalization and threshold-tuning.

Towards Efficient NLP: A Standard Evaluation and A Strong Baseline

1 code implementation • NAACL 2022 • Xiangyang Liu, Tianxiang Sun, Junliang He, Jiawen Wu, Lingling Wu, Xinyu Zhang, Hao Jiang, Zhao Cao, Xuanjing Huang, Xipeng Qiu

ELUE is dedicated to depict the Pareto Frontier for various language understanding tasks, such that it can tell whether and how much a method achieves Pareto improvement.