no code implementations • 25 Jun 2023 • Shuaicheng Zhang, Haohui Wang, Si Zhang, Dawei Zhou
While graph heterophily has been extensively studied in recent years, a fundamental research question largely remains nascent: How and to what extent will graph heterophily affect the prediction performance of graph neural networks (GNNs)?
1 code implementation • 1 May 2023 • Yue Wu, Shuaicheng Zhang, Wenchao Yu, Yanchi Liu, Quanquan Gu, Dawei Zhou, Haifeng Chen, Wei Cheng
The recent trend towards Personalized Federated Learning (PFL) has garnered significant attention as it allows for the training of models that are tailored to each client while maintaining data privacy.
1 code implementation • Findings (NAACL) 2022 • Shuaicheng Zhang, Lifu Huang, Qiang Ning
Extracting temporal relations (e. g., before, after, and simultaneous) among events is crucial to natural language understanding.
no code implementations • 12 Mar 2021 • Yusen Lin, Jiayong Lin, Shuaicheng Zhang, Haoying Dai
Recent studies have demonstrated a perceivable improvement on the performance of neural machine translation by applying cross-lingual language model pretraining (Lample and Conneau, 2019), especially the Translation Language Modeling (TLM).