no code implementations • 13 Mar 2024 • Zhenrong Cheng, Jiayan Guo, Hao Sun, Yan Zhang
In this study, we propose a lightweight data augmentation approach for disfluency detection, utilizing the superior generative and semantic understanding capabilities of large language model (LLM) to generate disfluent sentences as augmentation data.
1 code implementation • 6 Jun 2023 • Jiayan Guo, Lun Du, Xu Chen, Xiaojun Ma, Qiang Fu, Shi Han, Dongmei Zhang, Yan Zhang
Graph CF has attracted more and more attention in recent years due to its effectiveness in leveraging high-order information in the user-item bipartite graph for better recommendations.
no code implementations • 24 May 2023 • Jiayan Guo, Lun Du, Hengyu Liu, Mengyu Zhou, Xinyi He, Shi Han
In this study, we conduct an extensive investigation to assess the proficiency of LLMs in comprehending graph data, employing a diverse range of structural and semantic-related tasks.
no code implementations • 13 Feb 2023 • Jiayan Guo, Lun Du, Wendong Bi, Qiang Fu, Xiaojun Ma, Xu Chen, Shi Han, Dongmei Zhang, Yan Zhang
To this end, we propose HDHGR, a homophily-oriented deep heterogeneous graph rewiring approach that modifies the HG structure to increase the performance of HGNN.
1 code implementation • 26 Jun 2022 • Peiyan Zhang, Jiayan Guo, Chaozhuo Li, Yueqi Xie, Jaeboum Kim, Yan Zhang, Xing Xie, Haohan Wang, Sunghun Kim
Based on this observation, we intuitively propose to remove the GNN propagation part, while the readout module will take on more responsibility in the model reasoning process.
1 code implementation • 26 Jun 2022 • Jiayan Guo, Peiyan Zhang, Chaozhuo Li, Xing Xie, Yan Zhang, Sunghun Kim
Session-based recommendation (SBR) aims to predict the user next action based on the ongoing sessions.
no code implementations • 31 Jan 2022 • Jiayan Guo, Shangyang Li, Yue Zhao, Yan Zhang
Existing studies show that node representations generated by graph neural networks (GNNs) are vulnerable to adversarial attacks, such as unnoticeable perturbations of adjacent matrix and node features.
1 code implementation • 25 Dec 2021 • Jiayan Guo, Yaming Yang, Xiangchen Song, Yuan Zhang, Yujing Wang, Jing Bai, Yan Zhang
Specifically, we creatively propose Multi-granularity Intent Heterogeneous Session Graph which captures the interactions between different granularity intent units and relieves the burden of long-dependency.