Search Results for author: Xiaojun Ma

Found 11 papers, 2 papers with code

Text2Analysis: A Benchmark of Table Question Answering with Advanced Data Analysis and Unclear Queries

no code implementations21 Dec 2023 Xinyi He, Mengyu Zhou, Xinrun Xu, Xiaojun Ma, Rui Ding, Lun Du, Yan Gao, Ran Jia, Xu Chen, Shi Han, Zejian yuan, Dongmei Zhang

We evaluate five state-of-the-art models using three different metrics and the results show that our benchmark presents introduces considerable challenge in the field of tabular data analysis, paving the way for more advanced research opportunities.

Question Answering

On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering

1 code implementation6 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.

Collaborative Filtering Recommendation Systems

Enabling and Analyzing How to Efficiently Extract Information from Hybrid Long Documents with LLMs

no code implementations24 May 2023 Chongjian Yue, Xinrun Xu, Xiaojun Ma, Lun Du, Hengyu Liu, Zhiming Ding, Yanbing Jiang, Shi Han, Dongmei Zhang

We propose an Automated Financial Information Extraction (AFIE) framework that enhances LLMs' ability to comprehend and extract information from financial reports.

Retrieval

Hierarchical Transformer for Scalable Graph Learning

no code implementations4 May 2023 Wenhao Zhu, Tianyu Wen, Guojie Song, Xiaojun Ma, Liang Wang

Graph Transformer is gaining increasing attention in the field of machine learning and has demonstrated state-of-the-art performance on benchmarks for graph representation learning.

Graph Learning Graph Representation Learning

Homophily-oriented Heterogeneous Graph Rewiring

no code implementations13 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.

Graph Neural Network

LEReg: Empower Graph Neural Networks with Local Energy Regularization

no code implementations20 Mar 2022 Xiaojun Ma, Hanyue Chen, Guojie Song

With Intra-Energy Reg, we strengthen the message passing within each part, which is beneficial for getting more useful information.

Meta-Weight Graph Neural Network: Push the Limits Beyond Global Homophily

no code implementations19 Mar 2022 Xiaojun Ma, Qin Chen, Yuanyi Ren, Guojie Song, Liang Wang

These experiments show the excellent expressive power of MWGNN in dealing with graph data with various distributions.

Graph Neural Network

GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily

1 code implementation29 Oct 2021 Lun Du, Xiaozhou Shi, Qiang Fu, Xiaojun Ma, Hengyu Liu, Shi Han, Dongmei Zhang

For node-level tasks, GNNs have strong power to model the homophily property of graphs (i. e., connected nodes are more similar) while their ability to capture the heterophily property is often doubtful.

Graph Attention

Learning Discrete Adaptive Receptive Fields for Graph Convolutional Networks

no code implementations1 Jan 2021 Xiaojun Ma, Ziyao Li, Lingjun Xu, Guojie Song, Yi Li, Chuan Shi

To address this weakness, we introduce a novel framework of conducting graph convolutions, where nodes are discretely selected among multi-hop neighborhoods to construct adaptive receptive fields (ARFs).

EPNE: Evolutionary Pattern Preserving Network Embedding

no code implementations24 Sep 2020 Junshan Wang, Yilun Jin, Guojie Song, Xiaojun Ma

In this paper, we propose EPNE, a temporal network embedding model preserving evolutionary patterns of the local structure of nodes.

Network Embedding

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