Graph-Neural-networks-for-NLP

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Table of Contents
  1. Papers
  2. Code
  3. datasets
  4. Tutorials
  5. Researchers

Natural language processing

Papers

  • Graph Convolutional Networks for Text Classification

    • Liang Yao, Chengsheng Mao, Yuan Luo
    • [Paper]
  • Learning beyond Datasets: Knowledge Graph Augmented Neural Networks for Natural Language Processing

    • Annervaz K M, Somnath Basu Roy Chowdhury, Ambedkar Dukkipati
    • [Paper]
  • Multi-Label Text Classification using Attention-based Graph Neural Network

    • Ankit Pal, Muru Selvakumar, Malaikannan Sankarasubbu
    • [Paper]
  • Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks

    • Shikhar Vashishth, Manik Bhandari, Prateek Yadav, Piyush Rai, Chiranjib Bhattacharyya, Partha Talukdar
    • [Paper]
  • Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling

    • Diego Marcheggiani, Ivan Titov
    • [Paper]
  • A Shortest Path Dependency Kernel for Relation Extraction

    • Razvan Bunescu, Raymond Mooney
    • [Paper]
  • Graph Convolutional Encoders for Syntax-aware Neural Machine Translation

    • Jasmijn Bastings, Ivan Titov, Wilker Aziz, Diego Marcheggiani, Khalil Sima’an
    • [Paper]
  • Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks

    • Diego Marcheggiani, Jasmijn Bastings, Ivan Titov
    • [Paper]
  • Graph-to-Sequence Learning using Gated Graph Neural Networks

    • Daniel Beck, Gholamreza Haffari, Trevor Cohn
    • [Paper]
  • Recurrent Event Network : Global Structure Inference Over Temporal Knowledge Graph

    • Woojeong Jin, He Jiang, Meng Qu, Tong Chen, Changlin Zhang, Pedro Szekely, Xiang Ren
    • [Paper]
  • Jointly Multiple Events Extraction via Attention-based Graph Information Aggregation

    • Xiao Liu, Zhunchen Luo, Heyan Huang
    • [Paper]
  • AD3: Attentive Deep Document Dater

    • Swayambhu Nath Ray, Shib Sankar Dasgupta, Partha Talukdar
    • [Paper]
  • Dating Documents using Graph Convolution Networks

    • Shikhar Vashishth, Shib Sankar Dasgupta, Swayambhu Nath Ray, Partha Talukdar
    • [Paper]
  • Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network

    • Sunil Kumar Sahu, Fenia Christopoulou, Makoto Miwa, Sophia Ananiadou
    • [Paper]
  • GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction

    • Tsu-Jui Fu, Peng-Hsuan Li, Wei-Yun Ma
    • [Paper]
  • Attention Guided Graph Convolutional Networks for Relation Extraction

    • Zhijiang Guo, Yan Zhang, Wei Lu
    • [Paper]
  • Joint Type Inference on Entities and Relations via Graph Convolutional Networks

    • Changzhi Sun, Yeyun Gong, Yuanbin Wu, Ming Gong, Daxin Jiang, Man Lan, Shiliang Sun, Nan Duan
    • [Paper]
  • Graph Neural Networks with Generated Parameters for Relation Extraction

    • Hao Zhu, Yankai Lin, Zhiyuan Liu, Jie Fu, Tat-Seng Chua, Maosong Sun
    • [Paper]
  • Graph Convolution for Multimodal Information Extraction from Visually Rich Documents

    • Xiaojing Liu, Feiyu Gao, Qiong Zhang, Huasha Zhao
    • [Paper]
  • GraphIE: A Graph-Based Framework for Information Extraction

    • Yujie Qian, Enrico Santus, Zhijing Jin, Jiang Guo, Regina Barzilay
    • [Paper]
  • Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks

    • Ningyu Zhang, Shumin Deng, Zhanlin Sun, Guanying Wang, Xi Chen, Wei Zhang, Huajun Chen
    • [Paper]
  • Graph Convolution over Pruned Dependency Trees Improves Relation Extraction

    • Yuhao Zhang, Peng Qi, Christopher D. Manning
    • [Paper]
  • RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information

    • Shikhar Vashishth, Rishabh Joshi, Sai Suman Prayaga, Chiranjib Bhattacharyya, Partha Talukdar
    • [Paper]
  • Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs

    • Fenia Christopoulou, Makoto Miwa, Sophia Ananiadou
    • [Paper]
  • Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks

    • Shikhar Vashishth, Rishabh Joshi, Sai Suman Prayaga, Chiranjib Bhattacharyya, Partha Talukdar
    • [Paper]
  • Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks

    • Chen Zhang, Qiuchi Li, Dawei Song
    • [Paper]
  • DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation

    • Deepanway Ghosal, Navonil Majumder, Soujanya Poria, Niyati Chhaya, Alexander Gelbukh
    • [Paper]
  • Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification

    • Linmei Hu1 , Tianchi Yang, Chuan Shi, Houye Ji, Xiaoli Li
    • [Paper]
  • Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks

    • Shikhar Vashishth, Manik Bhandari, Prateek Yadav, Piyush Rai, Chiranjib Bhattacharyya, Partha Talukdar
    • [Paper]
  • Large-Scale Hierarchical Text Classification with Recursively Regularized Deep Graph-CNN

    • Hao Peng, Jianxin Li, Yu He, Yaopeng Liu, Mengjiao Bao, Lihong Wang , Yangqiu Song , Qiang Yang,
    • [Paper]
  • Jointly Multiple Events Extraction via Attention-based Graph Information Aggregation

    • Xiao Liu, Zhunchen Luo, Heyan Huang
    • [Paper]
  • Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network

    • Kun Xu, Liwei Wang, Mo Yu, Yansong Feng, Yan Song, Zhiguo Wang, Dong Yu
    • [Paper]
  • Multi-Channel Graph Neural Network for Entity Alignment

    • Yixin Cao, Zhiyuan Liu, Chengjiang Li, Zhiyuan Liu, Juanzi Li, Tat-Seng Chua
    • [Paper]
  • Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs

    • Yuting Wu, Xiao Liu, Yansong Feng, Zheng Wang, Rui Yan, Dongyan Zhao
    • [Paper]
  • A Vectorized Relational Graph Convolutional Network for Multi-Relational Network Alignment

    • Rui Ye, Xin Li, Yujie Fang, Hongyu Zang, Mingzhong Wang
    • [Paper]
  • Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs

    • Deepak Nathani, Jatin Chauhan, Charu Sharma, Manohar Kaul
    • [Paper]
  • Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding

    • Peifeng Wang, Jialong Han, Chenliang Li, Rong Pan
    • [Paper]
  • End-to-End Structure-Aware Convolutional Networks for Knowledge Base Completion

    • Chao Shang,Yun Tang, Jing Huang,Jinbo Bi,Xiaodong He,Bowen Zhou
    • [Paper]
  • One-Shot Relational Learning for Knowledge Graphs

    • Wenhan Xiong, Mo Yu, Shiyu Chang, Xiaoxiao Guo, William Yang Wang
    • [Paper]
  • Modeling Relational Data with Graph Convolutional Networks

    • Michael Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, Max Welling
    • [Paper]
  • Knowledge Transfer for Out-of-Knowledge-Base Entities : A Graph Neural Network Approach

    • Takuo Hamaguchi, Hidekazu Oiwa, Masashi Shimbo, Yuji Matsumoto
    • [Paper]
  • PaperRobot: Incremental Draft Generation of Scientific Ideas

    • Qingyun Wang, Lifu Huang, Zhiying Jiang, Kevin Knight, Heng Ji, Mohit Bansal, Yi Luan
    • [Paper]
  • Text Generation from Knowledge Graphs with Graph Transformers

    • Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, Mirella Lapata, Hannaneh Hajishirzi
    • [Paper]
  • Commonsense Knowledge Aware Conversation Generation with Graph Attention

    • Hao Zhou, Tom Young, Minlie Huang, Haizhou Zhao, Jingfang Xu, Xiaoyan Zhu
    • [Paper]
  • Towards Knowledge-Based Recommender Dialog System

    • Qibin Chen, Junyang Lin, Yichang Zhang, Ming Ding, Yukuo Cen, Hongxia Yang, Jie Tang
    • [Paper]
  • Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks

    • Namyong Park, Andrey Kan, Xin Luna Dong, Tong Zhao, Christos Faloutsos,
    • [Paper]
  • Deep Reasoning with Knowledge Graph for Social Relationship Understanding

    • Zhouxia Wang, Tianshui Chen, Jimmy Ren, Weihao Yu, Hui Cheng, Liang Lin
    • [Paper]
  • KGAT: Knowledge Graph Attention Network for Recommendation

    • Xiang Wang, Xiangnan He, Yixin Cao, Meng Liu, Tat-Seng Chua
    • [Paper]

    Ongoing list..