no code implementations • EMNLP 2021 • Zeru Zhang, Zijie Zhang, Yang Zhou, Lingfei Wu, Sixing Wu, Xiaoying Han, Dejing Dou, Tianshi Che, Da Yan
Recent literatures have shown that knowledge graph (KG) learning models are highly vulnerable to adversarial attacks.
no code implementations • 18 Dec 2023 • Ji Liu, Tianshi Che, Yang Zhou, Ruoming Jin, Huaiyu Dai, Dejing Dou, Patrick Valduriez
First, we propose an asynchronous FL system model with an efficient model aggregation method for improving the FL convergence.
1 code implementation • 23 Oct 2023 • Tianshi Che, Ji Liu, Yang Zhou, Jiaxiang Ren, Jiwen Zhou, Victor S. Sheng, Huaiyu Dai, Dejing Dou
This paper proposes a Parameter-efficient prompt Tuning approach with Adaptive Optimization, i. e., FedPepTAO, to enable efficient and effective FL of LLMs.