Search Results for author: Weizhi Xu

Found 10 papers, 7 papers with code

Heterogeneous Graph Reasoning for Fact Checking over Texts and Tables

1 code implementation20 Feb 2024 Haisong Gong, Weizhi Xu, Shu Wu, Qiang Liu, Liang Wang

To address this, we propose a novel word-level Heterogeneous-graph-based model for Fact Checking over unstructured and structured information, namely HeterFC.

Fact Checking Graph Neural Network +2

Starling: An I/O-Efficient Disk-Resident Graph Index Framework for High-Dimensional Vector Similarity Search on Data Segment

1 code implementation4 Jan 2024 Mengzhao Wang, Weizhi Xu, Xiaomeng Yi, Songlin Wu, Zhangyang Peng, Xiangyu Ke, Yunjun Gao, Xiaoliang Xu, Rentong Guo, Charles Xie

In this paper, we present Starling, an I/O-efficient disk-resident graph index framework that optimizes data layout and search strategy within the segment.

EX-FEVER: A Dataset for Multi-hop Explainable Fact Verification

1 code implementation15 Oct 2023 Huanhuan Ma, Weizhi Xu, Yifan Wei, Liuji Chen, Qiang Liu, Shu Wu, Liang Wang

Each instance is accompanied by a veracity label and an explanation that outlines the reasoning path supporting the veracity classification.

Claim Verification Explanation Generation +3

Adversarial Contrastive Learning for Evidence-aware Fake News Detection with Graph Neural Networks

1 code implementation11 Oct 2022 Junfei Wu, Weizhi Xu, Qiang Liu, Shu Wu, Liang Wang

Comprehensive experiments have demonstrated the superiority of GETRAL over the state-of-the-arts and validated the efficacy of semantic mining with graph structure and contrastive learning.

Contrastive Learning Fake News Detection +2

Application of Data Encryption in Chinese Named Entity Recognition

no code implementations31 Aug 2022 Kaifang Long, Jikun Dong, Shengyu Fan, Yanfang Geng, Yang Cao, Han Zhao, Hui Yu, Weizhi Xu

Recently, with the continuous development of deep learning, the performance of named entity recognition tasks has been dramatically improved.

Chinese Named Entity Recognition named-entity-recognition +1

Evidence-aware Fake News Detection with Graph Neural Networks

1 code implementation18 Jan 2022 Weizhi Xu, Junfei Wu, Qiang Liu, Shu Wu, Liang Wang

In this paper, we focus on the evidence-based fake news detection, where several evidences are utilized to probe the veracity of news (i. e., a claim).

Fake News Detection Graph structure learning

A Survey on Graph Structure Learning: Progress and Opportunities

no code implementations4 Mar 2021 Yanqiao Zhu, Weizhi Xu, Jinghao Zhang, Yuanqi Du, Jieyu Zhang, Qiang Liu, Carl Yang, Shu Wu

Specifically, we first formulate a general pipeline of GSL and review state-of-the-art methods classified by the way of modeling graph structures, followed by applications of GSL across domains.

Graph structure learning

Graph-based Hierarchical Relevance Matching Signals for Ad-hoc Retrieval

1 code implementation22 Feb 2021 Xueli Yu, Weizhi Xu, Zeyu Cui, Shu Wu, Liang Wang

In addition, due to the complexity and scale of the document collections, it is considerable to explore the different grain-sized hierarchical matching signals at a more general level.

Retrieval

When Contrastive Learning Meets Active Learning: A Novel Graph Active Learning Paradigm with Self-Supervision

no code implementations30 Oct 2020 Yanqiao Zhu, Weizhi Xu, Qiang Liu, Shu Wu

To this end, we present a minimax selection scheme that explicitly harnesses neighborhood information and discover homophilous subgraphs to facilitate active selection.

Active Learning Contrastive Learning +2

Accelerating convolutional neural network by exploiting sparsity on GPUs

3 code implementations22 Sep 2019 Weizhi Xu, Shengyu Fan, Hui Yu, Tiantian Wang, Yufeng Zhou

Multiplications and additions for zero values in the feature map are useless for convolution results.

Distributed, Parallel, and Cluster Computing

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