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.

• 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. 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]

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]

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, et al. EMNLP 2020 [pdf]
2. Language Generation with Multi-Hop Reasoning on Commonsense Knowledge Graph. Haozhe Ji, et al. EMNLP 2020 [pdf]
3. Learning to Represent Image and Text with Denotation Graph. Bowen Zhang, et al. EMNLP 2020 [pdf]
4. Double Graph Based Reasoning for Document-level Relation Extraction. Shuang Zeng, et al. EMNLP 2020 [pdf]
5. Knowledge Graph Alignment with Entity-Pair Embedding. Zhichun Wang, et al. EMNLP 2020 [pdf]
6. Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text Generation. Yan Zhang, et al. EMNLP 2020 [pdf]
7. Learn to Cross-lingual Transfer with Meta Graph Learning Across Heterogeneous Languages. Zheng Li, et al. EMNLP 2020 [pdf]
8. Multi-label Few/Zero-shot Learning with Knowledge Aggregated from Multiple Label Graphs. Jueqing Lu, et al. EMNLP 2020 [pdf]
9. Convolution over Hierarchical Syntactic and Lexical Graphs for Aspect Level Sentiment Analysis. Mi Zhang, et al. EMNLP 2020 [pdf]
10. Neural Extractive Summarization with Hierarchical Attentive Heterogeneous Graph Network. Ruipeng Jia, et al. EMNLP 2020 [pdf]
11. Neural Topic Modeling by Incorporating Document Relationship Graph. Deyu Zhou, et al. EMNLP 2020 [pdf]
12. Graph Convolutions over Constituent Trees for Syntax-Aware Semantic Role Labeling. Diego Marcheggiani, et al. EMNLP 2020 [pdf]
13. Improving Out-of-Scope Detection in Intent Classification by Using Embeddings of the Word Graph Space of the Classes. Paulo Cavalin, et al. EMNLP 2020 [pdf]
14. Keep It Surprisingly Simple: A Simple First Order Graph Based Parsing Model for Joint Morphosyntactic Parsing in Sanskrit. Amrith Krishna, et al. EMNLP 2020 [pdf]
15. Event Detection: Gate Diversity and Syntactic Importance Scores for Graph Convolution Neural Networks. Viet Dac Lai, et al. EMNLP 2020 [pdf]
16. Dynamic Anticipation and Completion for Multi-Hop Reasoning over Sparse Knowledge Graph. Xin Lv, et al. EMNLP 2020 [pdf]
17. Knowledge Association with Hyperbolic Knowledge Graph Embeddings. Zequn Sun, et al. EMNLP 2020 [pdf]
18. Structure Aware Negative Sampling in Knowledge Graphs. Kian Ahrabian, et al. EMNLP 2020 [pdf]
19. Recurrent Event Network: Autoregressive Structure Inferenceover Temporal Knowledge Graphs. Woojeong Jin, et al. EMNLP 2020 [pdf]
20. Question Directed Graph Attention Network for Numerical Reasoning over Text. Kunlong Chen, et al. EMNLP 2020 [pdf]
21. An Unsupervised Joint System for Text Generation from Knowledge Graphs and Semantic Parsing. Martin Schmitt, et al. EMNLP 2020 [pdf]
22. Message Passing for Hyper-Relational Knowledge Graphs. Mikhail Galkin, et al. EMNLP 2020 [pdf]
23. Relation-aware Graph Attention Networks with Relational Position Encodings for Emotion Recognition in Conversations. Taichi Ishiwatari, et al. EMNLP 2020 [pdf]
24. Program Enhanced Fact Verification with Verbalization and Graph Attention Network. Xiaoyu Yang, et al. EMNLP 2020 [pdf]
25. Text Graph Transformer for Document Classification. Haopeng Zhang, et al. EMNLP 2020 [pdf]
26. Learning Collaborative Agents with Rule Guidance for Knowledge Graph Reasoning. Deren Lei, et al. EMNLP 2020 [pdf]
27. Hierarchical Graph Network for Multi-hop Question Answering. Yuwei Fang, et al. EMNLP 2020 [pdf]
28. Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning. Tao Shen, et al. EMNLP 2020 [pdf]

COLING 2020

1. A Graph Representation of Semi-structured Data for Web Question Answering. Xingyao Zhang, et al. COLING 2020 [pdf]
2. Jointly Learning Aspect-Focused and Inter-Aspect Relations with Graph Convolutional Networks for Aspect Sentiment Analysis. Bin Liang, et al. COLING 2020 [pdf]
3. End-to-End Emotion-Cause Pair Extraction with Graph Convolutional Network. Ying Chen, et al. COLING 2020 [pdf]
4. Joint Aspect Extraction and Sentiment Analysis with Directional Graph Convolutional Networks. Guimin Chen, et al. COLING 2020 [pdf]
5. Heterogeneous Graph Neural Networks to Predict What Happen Next. Jianming Zheng, et al. COLING 2020 [pdf]
6. Improving Abstractive Dialogue Summarization with Graph Structures and Topic Words. Lulu Zhao, et al. COLING 2020 [pdf]
7. Knowledge Graph Embeddings in Geometric Algebras. Chengjin Xu, et al. COLING 2020 [pdf]
8. Exploiting Node Content for Multiview Graph Convolutional Network and Adversarial Regularization. Qiuhao Lu, et al. COLING 2020 [pdf]
9. Syntax-Aware Graph Attention Network for Aspect-Level Sentiment Classification. Lianzhe Huang, et al. COLING 2020 [pdf]
10. Aspect-Category based Sentiment Analysis with Hierarchical Graph Convolutional Network. Hongjie Cai, et al. COLING 2020 [pdf]
11. A High Precision Pipeline for Financial Knowledge Graph Construction. Sarah Elhammadi, et al. COLING 2020 [pdf]
12. Knowledge Graph Embedding with Atrous Convolution and Residual Learning. Feiliang Ren, et al. COLING 2020 [pdf]
13. Graph Enhanced Dual Attention Network for Document-Level Relation Extraction. Bo Li, et al. COLING 2020 [pdf]
14. Document-level Relation Extraction with Dual-tier Heterogeneous Graph. Zhenyu Zhang, et al. COLING 2020 [pdf]
15. Unsupervised Fact Checking by Counter-Weighted Positive and Negative Evidential Paths in A Knowledge Graph. Jiseong Kim, et al. COLING 2020 [pdf]
16. Multi-Task Learning for Knowledge Graph Completion with Pre-trained Language Models. Bosung Kim, et al. COLING 2020 [pdf]
17. Visual-Textual Alignment for Graph Inference in Visual Dialog. Tianling Jiang, et al. COLING 2020 [pdf]
18. Graph-Based Knowledge Integration for Question Answering over Dialogue. Jian Liu, et al. COLING 2020 [pdf]
19. Improving Commonsense Question Answering by Graph-based Iterative Retrieval over Multiple Knowledge Sources. Qianglong Chen, et al. COLING 2020 [pdf]
20. Automated Graph Generation at Sentence Level for Reading Comprehension Based on Conceptual Graphs. Wan-Hsuan Lin, et al. COLING 2020 [pdf]
21. Syntactic Graph Convolutional Network for Spoken Language Understanding. Keqing He, et al. COLING 2020 [pdf]
22. Normalizing Compositional Structures Across Graphbanks. Lucia Donatelli, et al. COLING 2020 [pdf]
23. Specializing Word Vectors by Spectral Decomposition on Heterogeneously Twisted Graphs. Yuanhang Ren, et al. COLING 2020 [pdf]
24. Summarize before Aggregate: A Global-to-local Heterogeneous Graph Inference Network for Conversational Emotion Recognition. Dongming Sheng, et al. COLING 2020 [pdf]
25. Suggest me a movie for tonight: Leveraging Knowledge Graphs for Conversational Recommendation. Rajdeep Sarkar, et al. COLING 2020 [pdf]
26. Integrating User History into Heterogeneous Graph for Dialogue Act Recognition. Dong Wang, et al. COLING 2020 [pdf]
27. Knowledge Graph Enhanced Neural Machine Translation via Multi-task Learning on Sub-entity Granularity. Yang Zhao, et al. COLING 2020 [pdf]
28. Global Context-enhanced Graph Convolutional Networks for Document-level Relation Extraction. Huiwei Zhou, et al. COLING 2020 [pdf]
29. Enhancing Extractive Text Summarization with Topic-Aware Graph Neural Networks. Peng Cui, et al. COLING 2020 [pdf]
30. Few-Shot Text Classification with Edge-Labeling Graph Neural Network-Based Prototypical Network. Chen Lyu, et al. COLING 2020 [pdf]
31. Fact-level Extractive Summarization with Hierarchical Graph Mask on BERT. Ruifeng Yuan, et al. COLING 2020 [pdf]
32. A Contextual Alignment Enhanced Cross Graph Attention Network for Cross-lingual Entity Alignment. Zhiwen Xie, et al. COLING 2020 [pdf]
33. Graph Convolution over Multiple Dependency Sub-graphs for Relation Extraction. Angrosh Mandya, et al. COLING 2020 [pdf]
34. Knowledge-Enhanced Natural Language Inference Based on Knowledge Graphs. Zikang Wang, et al. COLING 2020 [pdf]
35. Regularized Graph Convolutional Networks for Short Text Classification. Kshitij Tayal, et al. COLING 2020 [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.