Graph-Neural-networks-for-NLP

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..