A list of recent papers about GNN methods applied in NLP areas. Now, the repository includes papers published at ACL, EMNLP, NAACL-HLT, COLING, ICLR, WWW, ICML, KDD, and so on.

• May 24, 2021: Add NAACL-2021

• Dec 14, 2020: Add COLING-2020

• Dec 01, 2020: Add EMNLP-2020

• Jun 24, 2020: Add ACL-2020, GNN tools, and Ph.D. thesis.

1. Graph Neural Networks for Natural Language Processing: A Survey。[pdf]

1. Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks. Shikhar Vashishth, Manik Bhandari, Prateek Yadav, Piyush Rai, Chiranjib Bhattacharyya and Partha Talukdar. ACL 2019 [pdf] [code]

2. A Lexicon-Based Graph Neural Network for Chinese NER. Tao Gui, Yicheng Zou and Qi Zhang. EMNLP 2019 [pdf]

3. Look Again at the Syntax: Relational Graph Convolutional Network for Gendered Ambiguous Pronoun Resolution. Yinchuan Xu, Junlin Yang. GBNLP@ACL 2019 [pdf] [code]

1. Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks. Chen Zhang, Qiuchi Li and Dawei Song. EMNLP 2019 [pdf] [code]

2. Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification. Linmei Hu, Tianchi Yang, Chuan Shi, Houye Ji, Xiaoli Li. EMNLP 2019 [pdf]

3. Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks. Binxuan Huang and Kathleen M. Carley. EMNLP 2019 [pdf]

4. Relational Graph Attention Network for Aspect-based Sentiment Analysis. Kai Wang, Weizhou Shen, Yunyi Yang, Xiaojun Quan, Rui Wang. ACL 2020 [pdf]

1. BAG: Bi-directional Attention Entity Graph Convolutional Network for Multi-hop Reasoning Question Answering. Yu Cao, Meng Fang and Dacheng Tao. NAACL-HLT 2019. [pdf] [code]

2. Question Answering by Reasoning Across Documents with Graph Convolutional Networks. Nicola De Cao, Wilker Aziz and Ivan Titov. NAACL-HLT 2019. [pdf]

3. Cognitive Graph for Multi-Hop Reading Comprehension at Scale. Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang and Jie Tang. ACL 2019 [pdf] [code]

4. Dynamically Fused Graph Network for Multi-hop Reasoning. Yunxuan Xiao, Yanru Qu, Lin Qiu, Hao Zhou, Lei Li, Weinan Zhang and Yong Yu. ACL 2019 [pdf]

5. Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs. Ming Tu, Guangtao Wang, Jing Huang, Yun Tang, Xiaodong He and Bowen Zhou. ACL 2019 [pdf]

6. DialogueGCN A Graph Convolutional Neural Network for Emotion Recognition in Conversation. Deepanway Ghosal, Navonil Majumder, Soujanya Poria, Niyati Chhaya and Alexander Gelbukh. EMNLP 2019 [pdf]

7. GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification. Jie Zhou, Xu Han, Cheng Yang, Zhiyuan Liu, Lifeng Wang, Changcheng Li and Maosong Sun. ACL 2019 [pdf] [code]

8. Reasoning Over Semantic-Level Graph for Fact Checking. Wanjun Zhong, Jingjing Xu, Duyu Tang, Zenan Xu, Nan Duan, Ming Zhou, Jiahai Wang and Jian Yin. Arxiv 2019 [pdf]

9. Message Passing for Complex Question Answering over Knowledge Graphs. Svitlana Vakulenko, Javier David Fernandez Garcia, Axel Polleres, Maarten de Rijke, Michael Cochez. CIKM 2019 [pdf]

10. Knowledge-aware Textual Entailment with Graph Atention Network. Daoyuan Chen , Yaliang Li , Min Yang , Hai-Tao Zheng , Ying Shen. CIKM 2019 [pdf]

11. Fine-grained Fact Verification with Kernel Graph Attention Network. Zhenghao Liu, Chenyan Xiong, Maosong Sun, Zhiyuan Liu. ACL 2020 [pdf] [code]

1. Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks. Ningyu Zhang, Shumin Deng, Zhanlin Sun, Guanying Wang, Xi Chen, Wei Zhang and Huajun Chen. NAACL-HLT 2019. [pdf]

2. Attention Guided Graph Convolutional Networks for Relation Extraction. Zhijiang Guo, Yan Zhang and Wei Lu. ACL 2019 [pdf] [code]

3. Graph Neural Networks with Generated Parameters for Relation Extraction. Hao Zhu, Yankai Lin, Zhiyuan Liu, Jie Fu, Tat-seng Chua and Maosong Sun. ACL 2019 [pdf]

4. GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction. Tsu-Jui Fu, Peng-Hsuan Li and Wei-Yun Ma. ACL 2019 [pdf] [code]

1. Text Generation from Knowledge Graphs with Graph Transformers. Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, Mirella Lapata and Hannaneh Hajishirzi. NAACL-HLT 2019. [pdf] [code]

2. Coherent Comment Generation for Chinese Articles with a Graph-to-Sequence Model. Wei Li, Jingjing Xu, Yancheng He, Shengli Yan, Yunfang Wu and Xu Sun. ACL 2019 [pdf] [code]

3. Enhancing AMR-to-Text Generation with Dual Graph Representations. Leonardo F. R. Ribeiro, Claire Gardent and Iryna Gurevych. EMNLP 2019 [pdf]

4. Heterogeneous Graph Neural Networks for Extractive Document Summarization. Danqing Wang, Pengfei Liu, Yining Zheng, Xipeng Qiu, Xuanjing Huang. ACL 2020 [pdf] [code]

1. Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks. Namyong Park, Andrey Kan, Xin Luna Dong, Tong Zhao and Christos Faloutsos. KDD 2019 [pdf]

2. Hashing Graph Convolution for Node Classification. Wenting Zhao, Zhen Cui, Chunyan Xu, Chengzheng Li, Tong Zhang，Jian Yang. CIKM 2019 [pdf]

1. Abusive Language Detection with Graph Convolutional Networks. Pushkar Mishra, Marco Del Tredici, Helen Yannakoudakis and Ekaterina Shutova. NAACL-HLT 2019. [pdf]

2. Encoding Social Information with Graph Convolutional Networks for Political Perspective Detection in News Media. Chang Li and Dan Goldwasser. ACL 2019 [pdf]

3. Spam Review Detection with Graph Convolutional Networks. Ao Li, Zhou Qin, Runshi Liu, Yiqun Yang, Dong Li. CIKM 2019 [pdf]

4. Look before you Hop: Conversational Question Answering over Knowledge Graphs Using Judicious Context Expansion. Philipp Christmann, Rishiraj Saha Roy, Abdalghani Abujabal, Jyotsna Singh, Gerhard Weikum. CIKM 2019 [pdf]

5. GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media. Yi-Ju Lu, Cheng-Te Li. ACL 2020 [pdf]

1. Relation-Aware Graph Attention Network for Visual Question Answering. Linjie Li, Zhe Gan, Yu Cheng and Jingjing Liu. ICCV 2019 [pdf]

2. Language-Conditioned Graph Networks for Relational Reasoning. Ronghang Hu, Anna Rohrbach, Trevor Darrell and Kate Saenko. ICCV 2019 [pdf] [code]

3. Textbook Question Answering with Multi-modal Context Graph Understanding and Self-supervised Open-set Comprehension. Daesik Kim, Seonhoon Kim and Nojun Kwak. ACL 2019 [pdf]

4. Aligned Dual Channel Graph Convolutional Network for Visual Question Answering. Qingbao Huang, Jielong Wei, Yi Cai, Changmeng Zheng, Junying Chen, Ho-fung Leung, Qing Li. ACL 2020 [pdf]

5. Multimodal Neural Graph Memory Networks for Visual Question Answering. Mahmoud Khademi. ACL 2020 [pdf]

1. HetGNN: Heterogeneous Graph Neural Network. Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami and Nitesh V. Chawla. KDD 2019 [pdf]

2. GMNN: Graph Markov Neural Networks. Meng Qu, Yoshua Bengio and Jian Tang. ICML 2019 [pdf] [code]

NAACL-HLT 2019

1. BAG: Bi-directional Attention Entity Graph Convolutional Network for Multi-hop Reasoning Question Answering. Yu Cao, Meng Fang and Dacheng Tao. NAACL-HLT 2019. [pdf] [code]
2. Abusive Language Detection with Graph Convolutional Networks. Pushkar Mishra, Marco Del Tredici, Helen Yannakoudakis and Ekaterina Shutova. NAACL-HLT 2019. [pdf]
3. Text Generation from Knowledge Graphs with Graph Transformers. Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, Mirella Lapata and Hannaneh Hajishirzi. NAACL-HLT 2019. [pdf] [code]
4. Question Answering by Reasoning Across Documents with Graph Convolutional Networks. Nicola De Cao, Wilker Aziz and Ivan Titov. NAACL-HLT 2019. [pdf]
5. Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks. Ningyu Zhang, Shumin Deng, Zhanlin Sun, Guanying Wang, Xi Chen, Wei Zhang and Huajun Chen. NAACL-HLT 2019. [pdf]

KDD 2019

1. Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks. Namyong Park, Andrey Kan, Xin Luna Dong, Tong Zhao and Christos Faloutsos. KDD 2019 [pdf]
2. HetGNN: Heterogeneous Graph Neural Network. Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami and Nitesh V. Chawla. KDD 2019 [pdf]

ICML 2019

1. GMNN: Graph Markov Neural Networks. Meng Qu, Yoshua Bengio and Jian Tang. ICML 2019 [pdf] [code]

ICCV 2019

1. Relation-Aware Graph Attention Network for Visual Question Answering. Linjie Li, Zhe Gan, Yu Cheng and Jingjing Liu. ICCV 2019 [pdf]
2. Language-Conditioned Graph Networks for Relational Reasoning. Ronghang Hu, Anna Rohrbach, Trevor Darrell and Kate Saenko. ICCV 2019 [pdf] [code]

ACL 2019

1. Attention Guided Graph Convolutional Networks for Relation Extraction. Zhijiang Guo, Yan Zhang and Wei Lu. ACL 2019 [pdf] [code]
2. GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification. Jie Zhou, Xu Han, Cheng Yang, Zhiyuan Liu, Lifeng Wang, Changcheng Li and Maosong Sun. ACL 2019 [pdf] [code]
3. Cognitive Graph for Multi-Hop Reading Comprehension at Scale. Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang and Jie Tang. ACL 2019 [pdf] [code]
4. Coherent Comment Generation for Chinese Articles with a Graph-to-Sequence Model. Wei Li, Jingjing Xu, Yancheng He, Shengli Yan, Yunfang Wu and Xu Sun. ACL 2019 [pdf] [code]
5. Dynamically Fused Graph Network for Multi-hop Reasoning. Yunxuan Xiao, Yanru Qu, Lin Qiu, Hao Zhou, Lei Li, Weinan Zhang and Yong Yu. ACL 2019 [pdf]
6. Encoding Social Information with Graph Convolutional Networks for Political Perspective Detection in News Media. Chang Li and Dan Goldwasser. ACL 2019 [pdf]
7. Graph Neural Networks with Generated Parameters for Relation Extraction. Hao Zhu, Yankai Lin, Zhiyuan Liu, Jie Fu, Tat-seng Chua and Maosong Sun. ACL 2019 [pdf]
8. Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks. Shikhar Vashishth, Manik Bhandari, Prateek Yadav, Piyush Rai, Chiranjib Bhattacharyya and Partha Talukdar. ACL 2019 [pdf] [code]
9. GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction. Tsu-Jui Fu, Peng-Hsuan Li and Wei-Yun Ma. ACL 2019 [pdf] [code]
10. Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs. Ming Tu, Guangtao Wang, Jing Huang, Yun Tang, Xiaodong He and Bowen Zhou. ACL 2019 [pdf]
11. Textbook Question Answering with Multi-modal Context Graph Understanding and Self-supervised Open-set Comprehension. Daesik Kim, Seonhoon Kim and Nojun Kwak. ACL 2019 [pdf]
12. Look Again at the Syntax: Relational Graph Convolutional Network for Gendered Ambiguous Pronoun Resolution. Yinchuan Xu, Junlin Yang. GBNLP@ACL 2019 [pdf] [code]

EMNLP-IJCNLP 2019

1. A Lexicon-Based Graph Neural Network for Chinese NER. Tao Gui, Yicheng Zou and Qi Zhang. EMNLP 2019 [pdf]
2. Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks. Chen Zhang, Qiuchi Li and Dawei Song. EMNLP 2019 [pdf]
3. DialogueGCN A Graph Convolutional Neural Network for Emotion Recognition in Conversation. Deepanway Ghosal, Navonil Majumder, Soujanya Poria, Niyati Chhaya and Alexander Gelbukh. EMNLP 2019 [pdf]
4. Enhancing AMR-to-Text Generation with Dual Graph Representations. Leonardo F. R. Ribeiro, Claire Gardent and Iryna Gurevych. EMNLP 2019 [pdf]
5. Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification. Linmei Hu, Tianchi Yang, Chuan Shi, Houye Ji, Xiaoli Li. EMNLP 2019 [pdf]
6. Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks. Binxuan Huang and Kathleen M. Carley. EMNLP 2019 [pdf]

CIKM 2019

1. Spam Review Detection with Graph Convolutional Networks. Ao Li, Zhou Qin, Runshi Liu, Yiqun Yang, Dong Li. CIKM 2019 [pdf]
2. Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction. Zekun Li, Zeyu Cui, Shu Wu, Xiaoyu Zhang, Liang Wang. CIKM 2019 [pdf] [code]
3. Message Passing for Complex Question Answering over Knowledge Graphs. Svitlana Vakulenko, Javier David Fernandez Garcia, Axel Polleres, Maarten de Rijke, Michael Cochez. CIKM 2019 [pdf]
4. Knowledge-aware Textual Entailment with Graph Atention Network. Daoyuan Chen , Yaliang Li , Min Yang , Hai-Tao Zheng , Ying Shen. CIKM 2019 [pdf]
5. Look before you Hop: Conversational Question Answering over Knowledge Graphs Using Judicious Context Expansion. Philipp Christmann, Rishiraj Saha Roy, Abdalghani Abujabal, Jyotsna Singh, Gerhard Weikum. CIKM 2019 [pdf]
6. Cross-domain Aspect Category Transfer and Detection via Traceable Heterogeneous Graph Representation Learning. Zhuoren Jiang, Jian Wang, Lujun Zhao, Changlong Sun, Yao Lu, Xiaozhong Liu. CIKM 2019 [pdf]
7. Relation-Aware Graph Convolutional Networks for Agent-Initiated Social E-Commerce Recommendation. Fengli Xu , Jianxun Lian , Zhenyu Han , Yong Li , Yujian Xu , Xing Xie. CIKM 2019 [pdf]
8. Hashing Graph Convolution for Node Classification. Wenting Zhao, Zhen Cui, Chunyan Xu, Chengzheng Li, Tong Zhang，Jian Yang. CIKM 2019 [pdf]
9. Gravity-Inspired Graph Autoencoders for Directed Link Prediction. Guillaume Salha, Stratis Limnios, Romain Hennequin, Viet Anh Tran, Michalis Vazirgiannis. CIKM 2019 [pdf]
10. Multiple Rumor Source Detection with Graph Convolutional Networks. Ming Dong, Bolong Zheng, Nguyen Quoc Viet Hung, Han Su, Guohui Li. CIKM 2019 [pdf]

ICLR 2020

1. Memory-based Graph Networks. Amir hosein Khasahmadi, Kaveh Hassani, Parsa Moradi, Leo Lee, Quaid Morris. ICLR 2020 [pdf]
2. InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization. Fan-Yun Sun, Jordan Hoffman, Vikas Verma, Jian Tang. ICLR 2020 [pdf]
3. The Logical Expressiveness of Graph Neural Networks. Pablo Barceló, Egor V. Kostylev, Mikael Monet, Jorge Pérez, Juan Reutter, Juan Pablo Silva. ICLR 2020 [pdf]
4. Contrastive Learning of Structured World Models. Thomas Kipf, Elise van der Pol, Max Welling. ICLR 2020 [pdf] [code]
5. Geom-GCN: Geometric Graph Convolutional Networks. Hongbin Pei, Bingzhe Wei, Kevin Chen-Chuan Chang, Yu Lei, Bo Yang. ICLR 2020 [pdf]
6. Strategies for Pre-training Graph Neural Networks. Weihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay Pande, Jure Leskovec. ICLR 2020 [pdf]
7. Dynamically Pruned Message Passing Networks for Large-scale Knowledge Graph Reasoning. Xiaoran Xu, Wei Feng, Yunsheng Jiang, Xiaohui Xie, Zhiqing Sun, Zhi-Hong Deng. ICLR 2020 [pdf]
8. What graph neural networks cannot learn: depth vs width. Andreas Loukas. ICLR 2020 [pdf]
9. LambdaNet: Probabilistic Type Inference using Graph Neural Networks. Jiayi Wei, Maruth Goyal, Greg Durrett, Isil Dillig. ICLR 2020 [pdf]
10. Graph Convolutional Reinforcement Learning. Jiechuan Jiang, Chen Dun, Tiejun Huang, Zongqing Lu. ICLR 2020 [pdf]
11. DropEdge: Towards Deep Graph Convolutional Networks on Node Classification. Yu Rong, Wenbing Huang, Tingyang Xu, Junzhou Huang. ICLR 2020 [pdf]
12. Efficient Probabilistic Logic Reasoning with Graph Neural Networks. Yuyu Zhang, Xinshi Chen, Yuan Yang, Arun Ramamurthy, Bo Li, Yuan Qi, Le Song. ICLR 2020 [pdf]

WWW 2020

1. TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network. Jiaming Shen, Zhihong Shen, Chenyan Xiong, Chi Wang, Kuansan Wang, Jiawei Han. WWW 2020 [pdf]
2. Collective Multi-type Entity Alignment Between Knowledge Graphs. Qi Zhu, Hao Wei, Bunyamin Sisman, Da Zheng, Christos Faloutsos, Xin Luna Dong and Jiawei Han. WWW 2020 [pdf]
3. Complex Factoid Question Answering with a Free-Text Knowledge Graph. Chen Zhao, Chenyan Xiong, Xin Qian and Jordan Boyd-Graber. WWW 2020 [pdf]

ACL 2020

1. Fine-grained Fact Verification with Kernel Graph Attention Network. Zhenghao Liu, Chenyan Xiong, Maosong Sun, Zhiyuan Liu. ACL 2020 [pdf] [code]
2. GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media. Yi-Ju Lu, Cheng-Te Li. ACL 2020 [pdf]
3. Heterogeneous Graph Neural Networks for Extractive Document Summarization. Danqing Wang, Pengfei Liu, Yining Zheng, Xipeng Qiu, Xuanjing Huang. ACL 2020 [pdf] [code]
4. Relational Graph Attention Network for Aspect-based Sentiment Analysis. Kai Wang, Weizhou Shen, Yunyi Yang, Xiaojun Quan, Rui Wang. ACL 2020 [pdf] [code]
5. Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks. Yufeng Zhang∗ , Xueli Yu∗ , Zeyu Cui , Shu Wu, Zhongzhen Wen and Liang Wang. ACL 2020 [pdf] [code]
6. Integrating Semantic and Structural Information with Graph Convolutional Network for Controversy Detection. Lei Zhong, Juan Cao, Qiang Sheng, Junbo Guo, Ziang Wang. ACL 2020 [pdf] [code]
7. Line Graph Enhanced AMR-to-Text Generation with Mix-Order Graph Attention Networks. Yanbin Zhao, Lu Chen, Zhi Chen, Ruisheng Cao, Su Zhu, Kai Yu. ACL 2020 [pdf] [code]
8. Query Graph Generation for Answering Multi-hop Complex Questions from Knowledge Bases. Yunshi Lan, Jing Jiang. ACL 2020 [pdf] [code]
9. Semantic Graphs for Generating Deep Questions. Liangming Pan, Yuxi Xie, Yansong Feng, Tat-Seng Chua, Min-Yen Kan. ACL 2020 [pdf] [code]
10. Conversational Graph Grounded Policy Learning for Open-Domain Conversation Generation. Jun Xu, Haifeng Wang, Zheng-Yu Niu, Hua Wu, Wanxiang Che , Ting Liu. ACL 2020 [pdf]
11. Grounded Conversation Generation as Guided Traverses in Commonsense Knowledge Graphs. Houyu Zhang, Zhenghao Liu, Chenyan Xiong, Zhiyuan Liu. ACL 2020 [pdf] [code]
12. A Novel Graph-based Multi-modal Fusion Encoder for Neural Machine Translation. Yongjing Yin, Fandong Meng, Jinsong Su, Chulun Zhou, Zhengyuan Yang, Jie Zhou, Jiebo Luo. ACL 2020 [pdf] [code]
13. Syntax-Aware Opinion Role Labeling with Dependency Graph Convolutional Networks. Bo Zhang, Yue Zhang, Rui Wang, Zhenghua Li, Min Zhang. ACL 2020 [pdf]
14. A Graph-based Coarse-to-fine Method for Unsupervised Bilingual Lexicon Induction. Shuo Ren, Shujie Liu, Ming Zhou, Shuai Ma. ACL 2020 [pdf]
15. Graph Neural News Recommendation with Unsupervised Preference Disentanglement. Linmei Hu, Siyong Xu, Chen Li, Cheng Yang, Chuan Shi, Nan Duan, Xing Xie, Ming Zhou. ACL 2020 [pdf]
16. Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward. Luyang Huang, Lingfei Wu and Lu Wang. ACL 2020 [pdf] [code]
17. Entity-Aware Dependency-Based Deep Graph Attention Network for Comparative Preference Classification. Nianzu Ma, Sahisnu Mazumder, Hao Wang, Bing Liu. ACL 2020 [pdf]
18. LogicalFactChecker: Leveraging Logical Operations for Fact Checking with Graph Module Network. Wanjun Zhong , Duyu Tang, Zhangyin Feng , Nan Duan, Ming Zhou, Ming Gong, Linjun Shou, Daxin Jiang, Jiahai Wang and Jian Yin. ACL 2020 [pdf] [code]
19. Reasoning Over Semantic-Level Graph for Fact Checking. Wanjun Zhong, Jingjing Xu, Duyu Tang, Zenan Xu, Nan Duan, Ming Zhou, Jiahai Wang and Jian Yin. ACL 2020 [pdf]
20. Document Modeling with Graph Attention Networks for Multi-grained Machine Reading Comprehension. Bo Zheng, Haoyang Wen, Yaobo Liang, Nan Duan, Wanxiang Che, Daxin Jiang, Ming Zhou and Ting Liu. ACL 2020 [pdf] [code]
21. Heterogeneous Graph Transformer for Graph-to-Sequence Learning. Shaowei Yao, Tianming Wang, Xiaojun Wan. ACL 2020 [pdf] [code]
22. Aligned Dual Channel Graph Convolutional Network for Visual Question Answering. Qingbao Huang, Jielong Wei, Yi Cai, Changmeng Zheng, Junying Chen, Ho-fung Leung, Qing Li. ACL 2020 [pdf]
23. Multimodal Neural Graph Memory Networks for Visual Question Answering. Mahmoud Khademi. ACL 2020 [pdf]

EMNLP 2020

1. Connecting the Dots: Event Graph Schema Induction with Path Language Modeling. Manling Li, Qi Zeng, Ying Lin, Kyunghyun Cho, Heng Ji, Jonathan May, Nathanael Chambers and Clare Voss. EMNLP 2020 [pdf]
2. Language Generation with Multi-Hop Reasoning on Commonsense Knowledge Graph. Haozhe Ji, Pei Ke, Shaohan Huang, Furu Wei, Xiaoyan Zhu and Minlie Huang. EMNLP 2020 [pdf]
3. Learning to Represent Image and Text with Denotation Graph. Bowen Zhang, Hexiang Hu, Vihan Jain, Eugene Ie and Fei Sha. EMNLP 2020 [pdf]
4. ENT-DESC: Entity Description Generation by Exploring Knowledge Graph. Liying Cheng, Dekun Wu, Lidong Bing, Yan Zhang, Zhanming Jie, Wei Lu and Luo Si. EMNLP 2020 [pdf]
5. Double Graph Based Reasoning for Document-level Relation Extraction. Shuang Zeng, Runxin Xu, Baobao Chang and Lei Li. EMNLP 2020 [pdf]
6. Knowledge Graph Alignment with Entity-Pair Embedding. Zhichun Wang, Jinjian Yang and Xiaoju Ye. EMNLP 2020 [pdf]
7. Adaptive Attentional Network for Few-Shot Knowledge Graph Completion. Jiawei Sheng, Shu Guo, Zhenyu Chen, Juwei Yue, Lihong Wang, Tingwen Liu and Hongbo Xu. EMNLP 2020 [pdf]
8. GraphDialog: Integrating Graph Knowledge into End-to-End Task-Oriented Dialogue Systems. Shiquan Yang, Rui Zhang and Sarah Erfani. EMNLP 2020 [pdf]
9. Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text Generation. Yan Zhang, Zhijiang Guo, Zhiyang Teng, Wei Lu, Shay B. Cohen, Zuozhu Liu and Lidong Bing. EMNLP 2020 [pdf]
10. Learn to Cross-lingual Transfer with Meta Graph Learning Across Heterogeneous Languages. Zheng Li, Mukul Kumar, William Headden, Bing Yin, Ying Wei, Yu Zhang and Qiang Yang. EMNLP 2020 [pdf]
11. Disentangle-based Continual Graph Representation Learning. Xiaoyu Kou, Yankai Lin, Shaobo Liu, Peng Li, Jie Zhou and Yan Zhang. EMNLP 2020 [pdf]
12. Learning Physical Common Sense as Knowledge Graph Completion via BERT Data Augmentation and Constrained Tucker Factorization. Zhenjie Zhao, Evangelos Papalexakis and Xiaojuan Ma. EMNLP 2020 [pdf]
13. AttnIO: Knowledge Graph Exploration with In-and-Out Attention Flow for Knowledge-Grounded Dialogue. Jaehun Jung, Bokyung Son and Sungwon Lyu. EMNLP 2020 [pdf]
14. Neural Extractive Summarization with Hierarchical Attentive Heterogeneous Graph Network. Ruipeng Jia, Yanan Cao, Hengzhu Tang, Fang Fang, Cong Cao and Shi Wang. EMNLP 2020 [pdf]
15. Neural Topic Modeling by Incorporating Document Relationship Graph. Deyu Zhou, Xuemeng Hu and Rui Wang. EMNLP 2020 [pdf]
16. Graph Convolutions over Constituent Trees for Syntax-Aware Semantic Role Labeling. Diego Marcheggiani and Ivan Titov. EMNLP 2020 [pdf]
17. Improving Out-of-Scope Detection in Intent Classification by Using Embeddings of the Word Graph Space of the Classes. Paulo Cavalin, Victor Henrique Alves Ribeiro, Ana Appel and Claudio Pinhanez. EMNLP 2020 [pdf]
18. Keep it Surprisingly Simple: A Simple First Order Graph Based Parsing Model for Joint Morphosyntactic Parsing in Sanskrit. Amrith Krishna, Ashim Gupta, Deepak Garasangi, Pavankumar Satuluri and Pawan Goyal. EMNLP 2020 [pdf]
19. Event Detection: Gate Diversity and Syntactic Importance Scores for Graph Convolution Neural Networks. Viet Dac Lai, Tuan Ngo Nguyen and Thien Huu Nguyen. EMNLP 2020 [pdf]
20. Dynamic Anticipation and Completion for Multi-Hop Reasoning over Sparse Knowledge Graph. Xin Lv, Xu Han, Lei Hou, Juanzi Li, Zhiyuan Liu, Wei Zhang, Yichi Zhang, Hao Kong and Suhui Wu. EMNLP 2020 [pdf]
21. Knowledge Association with Hyperbolic Knowledge Graph Embeddings. Zequn Sun, Muhao Chen, Wei Hu, Chengming Wang, Jian Dai and Wei Zhang. EMNLP 2020 [pdf]
22. TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion. Jiapeng Wu, Meng Cao, Jackie Chi Kit Cheung and William L. Hamilton. EMNLP 2020 [pdf]
23. Supertagging Combinatory Categorial Grammar with Attentive Graph Convolutional Networks. Yuanhe Tian, Yan Song and Fei Xia. EMNLP 2020 [pdf]
24. Question Directed Graph Attention Network for Numerical Reasoning over Text. Kunlong Chen, Weidi Xu, Xingyi Cheng, Zou Xiaochuan, Yuyu Zhang, Le Song, Taifeng Wang, Yuan Qi and Wei Chu. EMNLP 2020 [pdf]
25. IGSQL: Database Schema Interaction Graph Based Neural Model for Context-Dependent Text-to-SQL Generation. Yitao Cai and Xiaojun Wan. EMNLP 2020 [pdf]
26. Is Graph Structure Necessary for Multi-hop Question Answering?. Nan Shao, Yiming Cui, Ting Liu, Shijin Wang and Guoping Hu. EMNLP 2020 [pdf]
27. DyERNIE: Dynamic Evolution of Riemannian Manifold Embeddings for Temporal Knowledge Graph Completion. Zhen Han, Peng Chen, Yunpu Ma and Volker Tresp. EMNLP 2020 [pdf]
28. Embedding Words in Non-Vector Space with Unsupervised Graph Learning. Max Ryabinin, Sergei Popov, Liudmila Prokhorenkova and Elena Voita. EMNLP 2020 [pdf]
29. Debiasing knowledge graph embeddings. Joseph Fisher, Arpit Mittal, Dave Palfrey and Christos Christodoulopoulos. EMNLP 2020 [pdf]
30. Relation-aware Graph Attention Networks with Relational Position Encodings for Emotion Recognition in Conversations. Taichi Ishiwatari, Yuki Yasuda, Taro Miyazaki and Jun Goto. EMNLP 2020 [pdf]
31. Program Enhanced Fact Verification with Verbalization and Graph Attention Network. Xiaoyu Yang, Feng Nie, Yufei Feng, Quan Liu, Zhigang Chen and Xiaodan Zhu. EMNLP 2020 [pdf]
32. VolTAGE: Volatility Forecasting via Text Audio Fusion with Graph Convolution Networks for Earnings Calls. Ramit Sawhney, Piyush Khanna, Arshiya Aggarwal, Taru Jain, Puneet Mathur and Rajiv Ratn Shah. EMNLP 2020 [pdf]
33. Evaluating the Calibration of Knowledge Graph Embeddings for Trustworthy Link Prediction. Tara Safavi, Danai Koutra and Edgar Meij. EMNLP 2020 [pdf]
34. Text Graph Transformer for Document Classification. Haopeng Zhang and Jiawei Zhang. EMNLP 2020 [pdf]
35. CoDEx: A Comprehensive Knowledge Graph Completion Benchmark. Tara Safavi and Danai Koutra. EMNLP 2020 [pdf]
36. Learning Collaborative Agents with Rule Guidance for Knowledge Graph Reasoning. Deren Lei, Gangrong Jiang, Xiaotao Gu, Kexuan Sun, Yuning Mao and Xiang Ren. EMNLP 2020 [pdf]
37. Hierarchical Graph Network for Multi-hop Question Answering. Yuwei Fang, Siqi Sun, Zhe Gan, Rohit Pillai, Shuohang Wang and Jingjing Liu. EMNLP 2020 [pdf]
38. SRLGRN: Semantic Role Labeling Graph Reasoning Network. Chen Zheng and Parisa Kordjamshidi. EMNLP 2020 [pdf]
39. LibKGE - A knowledge graph embedding library for reproducible research. Samuel Broscheit, Daniel Ruffinelli, Adrian Kochsiek, Patrick Betz and Rainer Gemulla. EMNLP 2020 [pdf]

COLING 2020

1. A Graph Representation of Semi-structured Data for Web Question Answering. Xingyao Zhang, Linjun Shou, Jian Pei, Ming Gong, Lijie Wen and Daxin Jiang. COLING 2020 [pdf]
2. Jointly Learning Aspect-Focused and Inter-Aspect Relations with Graph Convolutional Networks for Aspect Sentiment Analysis. Bin Liang, Rongdi Yin, Lin Gui, Jiachen Du and Ruifeng Xu. COLING 2020 [pdf]
3. End-to-End Emotion-Cause Pair Extraction with Graph Convolutional Network. Ying Chen, Wenjun Hou, Shoushan Li, Caicong Wu and Xiaoqiang Zhang. COLING 2020 [pdf]
4. Joint Aspect Extraction and Sentiment Analysis with Directional Graph Convolutional Networks. Guimin Chen, Yuanhe Tian and Yan Song. COLING 2020 [pdf]
5. Heterogeneous Graph Neural Networks to Predict What Happen Next. Jianming Zheng, Fei Cai, Yanxiang Ling and Honghui Chen. COLING 2020 [pdf]
6. Improving Abstractive Dialogue Summarization with Graph Structures and Topic Words. Lulu Zhao, Weiran Xu and Jun Guo. COLING 2020 [pdf]
7. AprilE: Attention with Pseudo Residual Connection for Knowledge Graph Embedding. Yuzhang Liu, Peng Wang, Yingtai Li, Yizhan Shao and Zhongkai Xu. COLING 2020 [pdf]
8. Knowledge Graph Embeddings in Geometric Algebras. Chengjin Xu, Mojtaba Nayyeri, Yung-Yu Chen and Jens Lehmann. COLING 2020 [pdf]
9. Exploiting Node Content for Multiview Graph Convolutional Network and Adversarial Regularization. Qiuhao Lu, Nisansa de Silva, Dejing Dou, Thien Huu Nguyen, Prithviraj Sen, Berthold Reinwald and Yunyao Li. COLING 2020 [pdf]
10. RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion. Hao Huang, Guodong Long, Tao Shen, Jing Jiang and Chengqi Zhang. COLING 2020 [pdf]
11. Syntax-Aware Graph Attention Network for Aspect-Level Sentiment Classification. Lianzhe Huang, Xin Sun, Sujian Li, Linhao Zhang and Houfeng Wang. COLING 2020 [pdf]
12. Aspect-Category based Sentiment Analysis with Hierarchical Graph Convolutional Network. Hongjie Cai, Yaofeng Tu, Xiangsheng Zhou, Jianfei Yu and Rui Xia. COLING 2020 [pdf]
13. A High Precision Pipeline for Financial Knowledge Graph Construction. Sarah Elhammadi, Laks V.S. Lakshmanan, Raymond Ng, Michael Simpson, Baoxing Huai, Zhefeng Wang and Lanjun Wang. COLING 2020 [pdf]
14. R-VGAE: Relational-variational Graph Autoencoder for Unsupervised Prerequisite Chain Learning. Irene Li, Alexander Fabbri, Swapnil Hingmire and Dragomir Radev. COLING 2020 [pdf]
15. Knowledge Graph Embedding with Atrous Convolution and Residual Learning. Feiliang Ren, Juchen Li, Huihui Zhang, Shilei Liu, Bochao Li, Ruicheng Ming and Yujia Bai. COLING 2020 [pdf]
16. Graph Enhanced Dual Attention Network for Document-Level Relation Extraction. Bo Li, Wei Ye, Zhonghao Sheng, Rui Xie, Xiangyu Xi and Shikun Zhang. COLING 2020 [pdf]
17. TeRo: A Time-aware Knowledge Graph Embedding via Temporal Rotation. Chengjin Xu, Mojtaba Nayyeri, Fouad Alkhoury, Hamed Shariat Yazdi and Jens Lehmann. COLING 2020 [pdf]
18. Document-level Relation Extraction with Dual-tier Heterogeneous Graph. Zhenyu Zhang, Bowen Yu, Xiaobo Shu, Tingwen Liu, Hengzhu Tang, Wang Yubin and Li Guo. COLING 2020 [pdf]
19. Unsupervised Fact Checking by Counter-Weighted Positive and Negative Evidential Paths in A Knowledge Graph. Jiseong Kim and Key-sun Choi. COLING 2020 [pdf]
20. Multi-Task Learning for Knowledge Graph Completion with Pre-trained Language Models. Bosung Kim, Taesuk Hong, Youngjoong Ko and Jungyun Seo. COLING 2020 [pdf]
21. Visual-Textual Alignment for Graph Inference in Visual Dialog. Tianling Jiang, Yi Ji, Chunping Liu and Hailin Shao. COLING 2020 [pdf]
22. I Know What You Asked: Graph Path Learning using AMR for Commonsense Reasoning. Jungwoo Lim, Dongsuk Oh, Yoonna Jang, Kisu Yang and Heuiseok Lim. COLING 2020 [pdf]
23. Modelling Long-distance Node Relations for KBQA with Global Dynamic Graph. Xu Wang, Shuai Zhao, Jiale Han, Bo Cheng, Hao Yang, Jianchang Ao and Zhenzi Li. COLING 2020 [pdf]
24. Automated Graph Generation at Sentence Level for Reading Comprehension Based on Conceptual Graphs. Wan-Hsuan Lin and Chun-Shien Lu. COLING 2020 [pdf]
25. Syntactic Graph Convolutional Network for Spoken Language Understanding. Keqing He, Shuyu Lei, Yushu Yang, Huixing Jiang and Zhongyuan Wang. COLING 2020 [pdf]
26. Summarize before Aggregate: A Global-to-local Heterogeneous Graph Inference Network for Conversational Emotion Recognition. Dongming Sheng, Dong Wang, Ying Shen, Haitao Zheng and Haozhuang Liu. COLING 2020 [pdf]
27. Integrating User History into Heterogeneous Graph for Dialogue Act Recognition. Dong Wang, Ziran Li, Haitao Zheng and Ying Shen. COLING 2020 [pdf]
28. Knowledge Graph Enhanced Neural Machine Translation via Multi-task Learning on Sub-entity Granularity. Yang Zhao, Lu Xiang, Junnan Zhu, Jiajun Zhang, Yu Zhou and Chengqing Zong. COLING 2020 [pdf]
29. Semi-supervised URL Segmentation with Recurrent Neural Networks Pre-trained on Knowledge Graph Entities. Hao Zhang, Jae Ro and Richard Sproat. COLING 2020 [pdf]
30. Global Context-enhanced Graph Convolutional Networks for Document-level Relation Extraction. Huiwei Zhou, Yibin Xu, Weihong Yao, Zhe Liu, Chengkun Lang and Haibin Jiang. COLING 2020 [pdf]
31. Enhancing Extractive Text Summarization with Topic-Aware Graph Neural Networks. Peng Cui, Le Hu and Yuanchao Liu. COLING 2020 [pdf]
32. Few-Shot Text Classification with Edge-Labeling Graph Neural Network-Based Prototypical Network. Chen Lyu, Weijie Liu and Ping Wang. COLING 2020 [pdf]
33. Fact-level Extractive Summarization with Hierarchical Graph Mask on BERT. Ruifeng Yuan, Zili Wang and Wenjie Li. COLING 2020 [pdf]
34. A Contextual Alignment Enhanced Cross Graph Attention Network for Cross-lingual Entity Alignment. Zhiwen Xie, Runjie Zhu, Kunsong Zhao, Jin Liu, Guangyou Zhou and Jimmy Xiangji Huang. COLING 2020 [pdf]
35. Graph Convolution over Multiple Dependency Sub-graphs for Relation Extraction. Angrosh Mandya, Danushka Bollegala and Frans Coenen. COLING 2020 [pdf]
36. Regularized Graph Convolutional Networks for Short Text Classification. Kshitij Tayal, Nikhil Rao, Saurabh Agarwal, Xiaowei Jia, Karthik Subbian and Vipin Kumar. COLING 2020 [pdf]

NAACL 2021

1. Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks. Minh Van Nguyen, Viet Lai and Thien Huu Nguyen. NAACL 2021 [pdf]
2. Abstract Meaning Representation Guided Graph Encoding and Decoding for Joint Information Extraction. Zixuan Zhang and Heng Ji. NAACL 2021 [pdf]
3. Event Time Extraction and Propagation via Graph Attention Networks. Haoyang Wen, Yanru Qu, Heng Ji, Qiang Ning, Jiawei Han, Avi Sil, Hanghang Tong and Dan Roth. NAACL 2021 [pdf]
4. SGL: Speaking the Graph Languages of Semantic Parsing via Multilingual Translation. Luigi Procopio, Rocco Tripodi and Roberto Navigli. NAACL 2021 [pdf]
5. Neural Language Modeling for Contextualized Temporal Graph Generation. Aman Madaan and Yiming Yang. NAACL 2021 [pdf]
6. Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning. Xuelu Chen, Michael Boratko, Muhao Chen, Shib Sankar Dasgupta, Xiang Lorraine Li and Andrew McCallum. NAACL 2021 [pdf]
7. MTAG: Modal-Temporal Attention Graph for Unaligned Human Multimodal Language Sequences. Jianing Yang, Yongxin Wang, Ruitao Yi, Yuying Zhu, Azaan Rehman, Amir Zadeh, Soujanya Poria and Louis-Philippe Morency. NAACL 2021 [pdf]
8. Incorporating Syntax and Semantics in Coreference Resolution with Heterogeneous Graph Attention Network. Fan Jiang and Trevor Cohn. NAACL 2021 [pdf]
9. Counterfactual Supporting Facts Extraction for Explainable Medical Record Based Diagnosis with Graph Network. Haoran Wu, Wei Chen, Shuang Xu and Bo Xu. NAACL 2021 [pdf]
10. Generating An Optimal Interview Question Plan Using A Knowledge Graph And Integer Linear Programming. Soham Datta, Prabir Mallick, Sangameshwar Patil, Indrajit Bhattacharya and Girish Palshikar. NAACL 2021 [pdf]
11. Heterogeneous Graph Neural Networks for Concept Prerequisite Relation Learning in Educational Data. Chenghao Jia, Yongliang Shen, Yechun Tang, Lu Sun and Weiming Lu. NAACL 2021 [pdf]
12. Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis. Xutan Peng, Guanyi Chen, Chenghua Lin and Mark Stevenson. NAACL 2021 [pdf]
13. Temporal Knowledge Graph Completion using a Linear Temporal Regularizer and Multivector Embeddings. Chengjin Xu, Yung-Yu Chen, Mojtaba Nayyeri and Jens Lehmann. NAACL 2021 [pdf]
14. Edge: Enriching Knowledge Graph Embeddings with External Text. Saed Rezayi, Handong Zhao, Sungchul Kim, Ryan Rossi, Nedim Lipka and Sheng Li. NAACL 2021 [pdf]
15. Graph Ensemble Learning over Multiple Dependency Trees for Aspect-level Sentiment Classification. Xiaochen Hou, Peng Qi, Guangtao Wang, Rex Ying, Jing Huang, Xiaodong He and Bowen Zhou. NAACL 2021 [pdf]
16. Aspect-based Sentiment Analysis with Type-aware Graph Convolutional Networks and Layer Ensemble. Yuanhe Tian, Guimin Chen and Yan Song. NAACL 2021 [pdf]
17. Graph Convolutional Networks for Event Causality Identification with Rich Document-level Structures. Minh Tran Phu and Thien Huu Nguyen. NAACL 2021 [pdf]
18. Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training. Oshin Agarwal, Heming Ge, Siamak Shakeri and Rami Al-Rfou. NAACL 2021 [pdf]
19. Inductive Topic Variational Graph Auto-Encoder for Text Classification. Qianqian Xie, Jimin Huang, Pan Du, Min Peng and Jian-Yun Nie. NAACL 2021 [pdf]
20. Efficiently Summarizing Text and Graph Encodings of Multi-Document Clusters. Ramakanth Pasunuru, Mengwen Liu, Mohit Bansal, Sujith Ravi and Markus Dreyer. NAACL 2021 [pdf]
21. Modeling Human Mental States with an Entity-based Narrative Graph. I-Ta Lee, Maria Leonor Pacheco and Dan Goldwasser. NAACL 2021 [pdf]
22. ShadowGNN: Graph Projection Neural Network for Text-to-SQL Parser. Zhi Chen, Lu Chen, Yanbin Zhao, Ruisheng Cao, Zihan Xu, Su Zhu and Kai Yu. NAACL 2021 [pdf]
23. RTFE: A Recursive Temporal Fact Embedding Framework for Temporal Knowledge Graph Completion. Youri Xu, Haihong E, Meina Song, Wenyu Song, Xiaodong Lv, Wang Haotian and Yang Jinrui. NAACL 2021 [pdf]
24. Breadth First Reasoning Graph for Multi-hop Question Answering. Yongjie Huang and Meng Yang. NAACL 2021 [pdf]
25. Improving Zero-Shot Cross-lingual Transfer for Multilingual Question Answering over Knowledge Graph. Yucheng Zhou, Xiubo Geng, Tao Shen, Wenqiang Zhang and Daxin Jiang. NAACL 2021 [pdf]
26. DAGN: Discourse-Aware Graph Network for Logical Reasoning. Yinya Huang, Meng Fang, Yu Cao, Liwei Wang and Xiaodan Liang. NAACL 2021 [pdf]

thunlp/GNNPapers

naganandy/graph-based-deep-learning-literature

nnzhan/Awesome-Graph-Neural-Networks

EMNLP 2019 GNNs-for-NLP

CS224W: Machine Learning with Graphs

Deep Graph Library (DGL)

PyTorch Geometric (PyG)

Natural Language Processing and Text Mining with Graph-Structured Representations, Bang Liu, University of Alberta.

Deep learning with graph-structured representations, Thomas Norbert Kipf, University of Amsterdam.

Neural Graph Embedding Methods for Natural Language Processing, Shikhar Vashishth, Indian Institute of Science.

The resurgence of structure in deep neural networks, Petar Veliˇckovi´c, University of Cambridge.