Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/graph4ai/graph4nlp_literature

This repo is to provide a list of literature regarding Deep Learning on Graphs for NLP
https://github.com/graph4ai/graph4nlp_literature

Last synced: 8 days ago
JSON representation

This repo is to provide a list of literature regarding Deep Learning on Graphs for NLP

Awesome Lists containing this project

README

        

# graph4nlp_literature
This repo is to provide a list of literature regarding Deep Learning on Graphs for NLP

- ## Dialogue Generation
- ### GNN for Directed Graphs
* #### IJCAI-19
[GSN: A Graph-Structured Network for Multi-Party Dialogues](https://www.ijcai.org/Proceedings/2019/696)

- ### App-driven
* #### IJCAI-19
[GSN: A Graph-Structured Network for Multi-Party Dialogues](https://www.ijcai.org/Proceedings/2019/696)

- ## Open-domain Question Answering
- ### GNN for Directed Graphs
* #### EMNLP-19
[PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text](https://www.aclweb.org/anthology/D19-1242/)

* #### EMNLP-20
[Open Domain Question Answering based on Text Enhanced Knowledge Graph with Hyperedge Infusion](https://www.aclweb.org/anthology/2020.findings-emnlp.133/)

* #### EMNLP-18
[Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text](https://www.aclweb.org/anthology/D18-1455/)

- ### Graph2Seq
* #### EMNLP-19
[PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text](https://www.aclweb.org/anthology/D19-1242/)

* #### EMNLP-20
[Open Domain Question Answering based on Text Enhanced Knowledge Graph with Hyperedge Infusion](https://www.aclweb.org/anthology/2020.findings-emnlp.133/)

* #### EMNLP-18
[Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text](https://www.aclweb.org/anthology/D18-1455/)

- ### Knowledge
* #### EMNLP-19
[PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text](https://www.aclweb.org/anthology/D19-1242/)

* #### EMNLP-20
[Open Domain Question Answering based on Text Enhanced Knowledge Graph with Hyperedge Infusion](https://www.aclweb.org/anthology/2020.findings-emnlp.133/)

* #### EMNLP-18
[Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text](https://www.aclweb.org/anthology/D18-1455/)

- ## Commonsense
- ### Knowledge
* #### IJCAI-18
[Commonsense Knowledge Aware Conversation Generation with Graph Attention](https://www.ijcai.org/Proceedings/2018/643)

- ## Knowledge Graph Alignment
- ### GNN for Directed Graphs
* #### ACL-19
[Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network](https://www.aclweb.org/anthology/P19-1304.pdf)

- ### GNN for Heterogeneous Graphs
* #### ACL-19
[Multi-Channel Graph Neural Network for Entity Alignment](https://www.aclweb.org/anthology/P19-1140.pdf)

* #### IJCAI-19
[A Vectorized Relational Graph Convolutional Network for Multi-Relational Network Alignment](https://www.ijcai.org/Proceedings/2019/0574.pdf)

[Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs](https://www.ijcai.org/Proceedings/2019/0733.pdf)

- ### GNN for Undirected Graphs
* #### AAAI-20
[Knowledge Graph Alignment Network with Gated Multi-Hop Neighborhood Aggregation](https://ojs.aaai.org//index.php/AAAI/article/view/5354)

[Coordinated Reasoning for Cross-Lingual Knowledge Graph Alignment](https://ojs.aaai.org//index.php/AAAI/article/view/6476)

* #### EMNLP-19
[Aligning Cross-Lingual Entities with Multi-Aspect Information](https://www.aclweb.org/anthology/D19-1451/)

[Semi-supervised Entity Alignment via Joint Knowledge Embedding Model and Cross-graph Model](https://www.aclweb.org/anthology/D19-1274.pdf)

[Jointly Learning Entity and Relation Representations for Entity Alignment](https://www.aclweb.org/anthology/D19-1023/)

* #### EMNLP-20
[Knowledge Graph Alignment with Entity-Pair Embedding](https://www.aclweb.org/anthology/2020.emnlp-main.130.pdf)

* #### EMNLP-18
[Cross-lingual Knowledge Graph Alignment via Graph Convolutional Networks](https://www.aclweb.org/anthology/D18-1032/)

- ### Knowledge
* #### AAAI-20
[Knowledge Graph Alignment Network with Gated Multi-Hop Neighborhood Aggregation](https://ojs.aaai.org//index.php/AAAI/article/view/5354)

[Coordinated Reasoning for Cross-Lingual Knowledge Graph Alignment](https://ojs.aaai.org//index.php/AAAI/article/view/6476)

* #### ACL-19
[Multi-Channel Graph Neural Network for Entity Alignment](https://www.aclweb.org/anthology/P19-1140.pdf)

[Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network](https://www.aclweb.org/anthology/P19-1304.pdf)

* #### EMNLP-19
[Aligning Cross-Lingual Entities with Multi-Aspect Information](https://www.aclweb.org/anthology/D19-1451/)

[Semi-supervised Entity Alignment via Joint Knowledge Embedding Model and Cross-graph Model](https://www.aclweb.org/anthology/D19-1274.pdf)

[Jointly Learning Entity and Relation Representations for Entity Alignment](https://www.aclweb.org/anthology/D19-1023/)

* #### EMNLP-20
[Knowledge Graph Alignment with Entity-Pair Embedding](https://www.aclweb.org/anthology/2020.emnlp-main.130.pdf)

* #### IJCAI-19
[A Vectorized Relational Graph Convolutional Network for Multi-Relational Network Alignment](https://www.ijcai.org/Proceedings/2019/0574.pdf)

[Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs](https://www.ijcai.org/Proceedings/2019/0733.pdf)

* #### EMNLP-18
[Cross-lingual Knowledge Graph Alignment via Graph Convolutional Networks](https://www.aclweb.org/anthology/D18-1032/)

- ## Named-entity Recognition
- ### Node Embedding Based Refined
* #### NAACL-19
[A General Framework for Information Extraction using Dynamic Span Graphs](https://www.aclweb.org/anthology/N19-1308.pdf)

- ### Coreference
* #### NAACL-19
[A General Framework for Information Extraction using Dynamic Span Graphs](https://www.aclweb.org/anthology/N19-1308.pdf)

- ### Dependency
* #### ACL-19
[GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction](https://www.aclweb.org/anthology/P19-1136.pdf)

- ### GNN for Directed Graphs
* #### ACL-20
[Bipartite Flat-Graph Network for Nested Named Entity Recognition](https://www.aclweb.org/anthology/2020.acl-main.571.pdf)

* #### ACL-19
[A Neural Multi-digraph Model for Chinese NER with Gazetteers](https://www.aclweb.org/anthology/P19-1141.pdf)

- ### App-driven
* #### ACL-20
[Bipartite Flat-Graph Network for Nested Named Entity Recognition](https://www.aclweb.org/anthology/2020.acl-main.571.pdf)

* #### ACL-19
[A Neural Multi-digraph Model for Chinese NER with Gazetteers](https://www.aclweb.org/anthology/P19-1141.pdf)

* #### EMNLP-19
[A Lexicon-Based Graph Neural Network for Chinese NER](https://www.aclweb.org/anthology/D19-1096.pdf)

- ### GNN for Heterogeneous Graphs
* #### ACL-19
[GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction](https://www.aclweb.org/anthology/P19-1136.pdf)

* #### EMNLP-19
[A Lexicon-Based Graph Neural Network for Chinese NER](https://www.aclweb.org/anthology/D19-1096.pdf)

- ### GNN for Undirected Graphs
* #### EMNLP-19
[Leverage Lexical Knowledge for Chinese Named Entity Recognition via Collaborative Graph Network](https://www.aclweb.org/anthology/D19-1396/)

- ### Knowledge
* #### EMNLP-19
[Leverage Lexical Knowledge for Chinese Named Entity Recognition via Collaborative Graph Network](https://www.aclweb.org/anthology/D19-1396/)

- ## AMR2Text
- ### Graph2Graph
* #### EMNLP-20
[Online Back-Parsing for AMR-to-Text Generation](https://www.aclweb.org/anthology/2020.emnlp-main.92/)

- ### Dependency
* #### ACL-18
[Graph-to-Sequence Learning using Gated Graph Neural Networks](https://www.aclweb.org/anthology/P18-1026/)

- ### GNN for Directed Graphs
* #### AAAI-20
[Graph Transformer for Graph-to-Sequence Learning](https://ojs.aaai.org//index.php/AAAI/article/view/6243)

* #### COLING-20
[Generalized Shortest-Paths Encoders for AMR-to-Text Generation](https://www.aclweb.org/anthology/2020.coling-main.181.pdf)

* #### ACL-20
[Structural Information Preserving for Graph-to-Text Generation](https://www.aclweb.org/anthology/2020.acl-main.712/)

[Line Graph Enhanced AMR-to-Text Generation with Mix-Order Graph Attention Networks](https://www.aclweb.org/anthology/2020.acl-main.67/)

* #### ACL-19
[Modeling Graph Structure in Transformer for Better AMR-to-Text Generation](https://www.aclweb.org/anthology/D19-1548/)

* #### TACL-20
[AMR-To-Text Generation with Graph Transformer](https://www.aclweb.org/anthology/2020.tacl-1.2.pdf)

* #### EMNLP-19
[Enhancing AMR-to-Text Generation with Dual Graph Representations](https://www.aclweb.org/anthology/D19-1314/)

* #### EMNLP-20
[Online Back-Parsing for AMR-to-Text Generation](https://www.aclweb.org/anthology/2020.emnlp-main.92/)

[Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text Generation](https://www.aclweb.org/anthology/2020.emnlp-main.169/)

* #### ACL-18
[Graph-to-Sequence Learning using Gated Graph Neural Networks](https://www.aclweb.org/anthology/P18-1026/)

[A Graph-to-Sequence Model for AMR-to-Text Generation](https://www.aclweb.org/anthology/P18-1150/)

* #### NAACL-19
[Structural Neural Encoders for AMR-to-text Generation](https://www.aclweb.org/anthology/N19-1366/)

* #### IJCAI-20
[Better AMR-To-Text Generation with Graph Structure Reconstruction](https://www.ijcai.org/Proceedings/2020/0542.pdf)

* #### TACL-19
[Semantic neural machine translation using AMR](https://www.aclweb.org/anthology/Q19-1002.pdf)

- ### AMR
* #### AAAI-20
[Graph Transformer for Graph-to-Sequence Learning](https://ojs.aaai.org//index.php/AAAI/article/view/6243)

* #### COLING-20
[Generalized Shortest-Paths Encoders for AMR-to-Text Generation](https://www.aclweb.org/anthology/2020.coling-main.181.pdf)

* #### ACL-20
[Heterogeneous Graph Transformer for Graph-to-Sequence Learning](https://www.aclweb.org/anthology/2020.acl-main.640.pdf)

[Structural Information Preserving for Graph-to-Text Generation](https://www.aclweb.org/anthology/2020.acl-main.712/)

[Line Graph Enhanced AMR-to-Text Generation with Mix-Order Graph Attention Networks](https://www.aclweb.org/anthology/2020.acl-main.67/)

* #### ACL-19
[Modeling Graph Structure in Transformer for Better AMR-to-Text Generation](https://www.aclweb.org/anthology/D19-1548/)

* #### TACL-20
[AMR-To-Text Generation with Graph Transformer](https://www.aclweb.org/anthology/2020.tacl-1.2.pdf)

* #### EMNLP-19
[Enhancing AMR-to-Text Generation with Dual Graph Representations](https://www.aclweb.org/anthology/D19-1314/)

* #### EMNLP-20
[Online Back-Parsing for AMR-to-Text Generation](https://www.aclweb.org/anthology/2020.emnlp-main.92/)

[Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text Generation](https://www.aclweb.org/anthology/2020.emnlp-main.169/)

* #### ACL-18
[Graph-to-Sequence Learning using Gated Graph Neural Networks](https://www.aclweb.org/anthology/P18-1026/)

[A Graph-to-Sequence Model for AMR-to-Text Generation](https://www.aclweb.org/anthology/P18-1150/)

* #### NAACL-19
[Structural Neural Encoders for AMR-to-text Generation](https://www.aclweb.org/anthology/N19-1366/)

* #### IJCAI-20
[Better AMR-To-Text Generation with Graph Structure Reconstruction](https://www.ijcai.org/Proceedings/2020/0542.pdf)

* #### TACL-19
[Semantic neural machine translation using AMR](https://www.aclweb.org/anthology/Q19-1002.pdf)

[Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning](https://www.aclweb.org/anthology/Q19-1019/)

- ### GNN for Heterogeneous Graphs
* #### ACL-20
[Heterogeneous Graph Transformer for Graph-to-Sequence Learning](https://www.aclweb.org/anthology/2020.acl-main.640.pdf)

- ### Graph2Seq
* #### AAAI-20
[Graph Transformer for Graph-to-Sequence Learning](https://ojs.aaai.org//index.php/AAAI/article/view/6243)

* #### COLING-20
[Generalized Shortest-Paths Encoders for AMR-to-Text Generation](https://www.aclweb.org/anthology/2020.coling-main.181.pdf)

* #### ACL-20
[Heterogeneous Graph Transformer for Graph-to-Sequence Learning](https://www.aclweb.org/anthology/2020.acl-main.640.pdf)

[Structural Information Preserving for Graph-to-Text Generation](https://www.aclweb.org/anthology/2020.acl-main.712/)

[Line Graph Enhanced AMR-to-Text Generation with Mix-Order Graph Attention Networks](https://www.aclweb.org/anthology/2020.acl-main.67/)

* #### ACL-19
[Modeling Graph Structure in Transformer for Better AMR-to-Text Generation](https://www.aclweb.org/anthology/D19-1548/)

* #### TACL-20
[AMR-To-Text Generation with Graph Transformer](https://www.aclweb.org/anthology/2020.tacl-1.2.pdf)

* #### EMNLP-19
[Enhancing AMR-to-Text Generation with Dual Graph Representations](https://www.aclweb.org/anthology/D19-1314/)

* #### EMNLP-20
[Online Back-Parsing for AMR-to-Text Generation](https://www.aclweb.org/anthology/2020.emnlp-main.92/)

[Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text Generation](https://www.aclweb.org/anthology/2020.emnlp-main.169/)

* #### ACL-18
[Graph-to-Sequence Learning using Gated Graph Neural Networks](https://www.aclweb.org/anthology/P18-1026/)

[A Graph-to-Sequence Model for AMR-to-Text Generation](https://www.aclweb.org/anthology/P18-1150/)

* #### NAACL-19
[Structural Neural Encoders for AMR-to-text Generation](https://www.aclweb.org/anthology/N19-1366/)

* #### IJCAI-20
[Better AMR-To-Text Generation with Graph Structure Reconstruction](https://www.ijcai.org/Proceedings/2020/0542.pdf)

* #### TACL-19
[Semantic neural machine translation using AMR](https://www.aclweb.org/anthology/Q19-1002.pdf)

[Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning](https://www.aclweb.org/anthology/Q19-1019/)

- ### GNN for Undirected Graphs
* #### TACL-19
[Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning](https://www.aclweb.org/anthology/Q19-1019/)

- ### Knowledge
* #### ACL-20
[Structural Information Preserving for Graph-to-Text Generation](https://www.aclweb.org/anthology/2020.acl-main.712/)

- ## Math Word Problem
- ### Dependency
* #### EMNLP-20
[Graph-to-Tree Neural Networksfor Learning Structured Input-Output Translationwith Applications to Semantic Parsing and Math Word Problem](https://www.aclweb.org/anthology/2020.findings-emnlp.255/)

- ### GNN for Directed Graphs
* #### EMNLP-20
[Graph-to-Tree Neural Networksfor Learning Structured Input-Output Translationwith Applications to Semantic Parsing and Math Word Problem](https://www.aclweb.org/anthology/2020.findings-emnlp.255/)

- ### App-driven
* #### ACL-20
[Graph-to-Tree Learning for Solving Math Word Problems](https://www.aclweb.org/anthology/2020.acl-main.362/)

[Premise Selection in Natural Language Mathematical Texts](https://www.aclweb.org/anthology/2020.acl-main.657/)

* #### ICLR-20
[Mathematical Reasoning in Latent Space](https://openreview.net/forum?id=Ske31kBtPr)

- ### GNN for Heterogeneous Graphs
* #### EMNLP-20
[Graph-to-Tree Neural Networksfor Learning Structured Input-Output Translationwith Applications to Semantic Parsing and Math Word Problem](https://www.aclweb.org/anthology/2020.findings-emnlp.255/)

- ### Constituency
* #### EMNLP-20
[Graph-to-Tree Neural Networksfor Learning Structured Input-Output Translationwith Applications to Semantic Parsing and Math Word Problem](https://www.aclweb.org/anthology/2020.findings-emnlp.255/)

- ### Knowledge
* #### ACL-20
[A Knowledge-Aware Sequence-to-Tree Network for Math Word Problem Solving](https://www.aclweb.org/anthology/2020.emnlp-main.579/)

- ### Graph2Tree
* #### ACL-20
[A Knowledge-Aware Sequence-to-Tree Network for Math Word Problem Solving](https://www.aclweb.org/anthology/2020.emnlp-main.579/)

[Graph-to-Tree Learning for Solving Math Word Problems](https://www.aclweb.org/anthology/2020.acl-main.362/)

* #### EMNLP-20
[Graph-to-Tree Neural Networksfor Learning Structured Input-Output Translationwith Applications to Semantic Parsing and Math Word Problem](https://www.aclweb.org/anthology/2020.findings-emnlp.255/)

- ## Topic Modeling
- ### Co-occurrence
* #### EMNLP-18
[GraphBTM: Graph Enhanced Autoencoded Variational Inference for Biterm Topic Model](https://www.aclweb.org/anthology/D18-1495)

- ### GNN for Directed Graphs
* #### WWW-20
[Graph Attention Topic Modeling Network](http://doi.org/10.1145/3366423.3380102)

* #### EMNLP-18
[GraphBTM: Graph Enhanced Autoencoded Variational Inference for Biterm Topic Model](https://www.aclweb.org/anthology/D18-1495)

- ### GNN on Directed Graphs
* #### EMNLP-20
[Neural Topic Modeling by Incorporating Document Relationship Graph](https://www.aclweb.org/anthology/2020.emnlp-main.310)

- ### Topic
* #### KDD-20
[Graph Structural-topic Neural Network](http://doi.org/10.1145/3394486.3403150)

* #### ACL-20
[Tree-Structured Neural Topic Model](https://www.aclweb.org/anthology/2020.acl-main.73/)

* #### EMNLP-20
[Neural Topic Modeling by Incorporating Document Relationship Graph](https://www.aclweb.org/anthology/2020.emnlp-main.310)

- ## Dialogue State Tracking
- ### GNN for Directed Graphs
* #### COLING-19
[Structured Dialogue Policy with Graph Neural Networks](https://www.aclweb.org/anthology/C18-1107/)

- ### App-driven
* #### AAAI-20
[Schema-Guided Multi-Domain Dialogue State Tracking with Graph Attention Neural Networks](https://ojs.aaai.org//index.php/AAAI/article/view/6250)

- ### GNN for Heterogeneous Graphs
* #### AAAI-20
[Schema-Guided Multi-Domain Dialogue State Tracking with Graph Attention Neural Networks](https://ojs.aaai.org//index.php/AAAI/article/view/6250)

- ### Node Embedding Based
* #### COLING-19
[Structured Dialogue Policy with Graph Neural Networks](https://www.aclweb.org/anthology/C18-1107/)

- ## Parsing
- ### GNN for Directed Graphs
* #### NeurIPS-20
[Strongly Incremental Constituency Parsing with Graph Neural Networks](https://proceedings.neurips.cc/paper/2020/hash/f7177163c833dff4b38fc8d2872f1ec6-Abstract.html)

- ### Constituency
* #### NeurIPS-20
[Strongly Incremental Constituency Parsing with Graph Neural Networks](https://proceedings.neurips.cc/paper/2020/hash/f7177163c833dff4b38fc8d2872f1ec6-Abstract.html)

- ## Entity Typing in KB
- ### GNN for Undirected Graphs
* #### EMNLP-19
[Fine-Grained Entity Typing via Hierarchical Multi Graph Convolutional Networks](https://www.aclweb.org/anthology/D19-1502.pdf)

- ### Knowledge
* #### EMNLP-19
[Fine-Grained Entity Typing via Hierarchical Multi Graph Convolutional Networks](https://www.aclweb.org/anthology/D19-1502.pdf)

- ## Dependency Parsing
- ### Dependency
* #### ACL-20
[Neural Reranking for Dependency Parsing: An Evaluation](https://www.aclweb.org/anthology/2020.acl-main.379/)

- ### GNN for Directed Graphs
* #### ACL-20
[Neural Reranking for Dependency Parsing: An Evaluation](https://www.aclweb.org/anthology/2020.acl-main.379/)

- ### App-driven
* #### ACL-19
[Graph-based Dependency Parsing with Graph Neural Networks](https://www.aclweb.org/anthology/P19-1237/)

- ### GNN for Undirected Graphs
* #### ACL-19
[Graph-based Dependency Parsing with Graph Neural Networks](https://www.aclweb.org/anthology/P19-1237/)

- ### Graph2Tree
* #### ACL-19
[Graph-based Dependency Parsing with Graph Neural Networks](https://www.aclweb.org/anthology/P19-1237/)

- ## Text Matching
- ### GNN for Directed Graphs
* #### ACL-20
[Neural Graph Matching Networks for Chinese Short Text Matching](https://www.aclweb.org/anthology/2020.acl-main.547/)

- ### App-driven
* #### ACL-20
[Neural Graph Matching Networks for Chinese Short Text Matching](https://www.aclweb.org/anthology/2020.acl-main.547/)

[Matching Article Pairs with Graphical Decomposition and Convolutions](https://arxiv.org/abs/1802.07459)

- ### GNN for Undirected Graphs
* #### ACL-20
[Matching Article Pairs with Graphical Decomposition and Convolutions](https://arxiv.org/abs/1802.07459)

- ## Question Generation
- ### Dependency
* #### WWW-19
[Learning to Generate Questions by Learning What not to Generate](https://dl.acm.org/doi/10.1145/3308558.3313737)

* #### COLING-20
[Answer-driven Deep Question Generation based on Reinforcement Learning](https://www.aclweb.org/anthology/2020.coling-main.452/)

* #### ICLR-20
[Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation](https://openreview.net/pdf?id=HygnDhEtvr)

- ### GNN for Directed Graphs
* #### ICLR-20
[Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation](https://openreview.net/pdf?id=HygnDhEtvr)

- ### Node Embedding Based
* #### ICLR-20
[Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation](https://openreview.net/pdf?id=HygnDhEtvr)

- ### Graph2Seq
* #### COLING-20
[Answer-driven Deep Question Generation based on Reinforcement Learning](https://www.aclweb.org/anthology/2020.coling-main.452/)

* #### ICLR-20
[Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation](https://openreview.net/pdf?id=HygnDhEtvr)

- ### GNN for Undirected Graphs
* #### WWW-19
[Learning to Generate Questions by Learning What not to Generate](https://dl.acm.org/doi/10.1145/3308558.3313737)

* #### COLING-20
[Answer-driven Deep Question Generation based on Reinforcement Learning](https://www.aclweb.org/anthology/2020.coling-main.452/)

- ## Next Utterance Prediction
- ### App-driven
* #### AAAI-21
[A Graph Reasoning Network for Multi-turn Response Selection via Customized Pre-training](https://arxiv.org/abs/2012.11099)

- ### GNN for Undirected Graphs
* #### AAAI-21
[A Graph Reasoning Network for Multi-turn Response Selection via Customized Pre-training](https://arxiv.org/abs/2012.11099)

- ## Code Summarization
- ### GNN for Directed Graphs
* #### ArXiv-20
[Improved code summarization via a graph neural network](https://arxiv.org/pdf/2004.02843.pdf)

* #### ICLR-18
[learning to represent programs with graphs](https://openreview.net/pdf?id=BJOFETxR-)

* #### ICLR-19
[Structured Neural Summarization](https://openreview.net/pdf?id=H1ersoRqtm)

- ### App-driven
* #### ArXiv-20
[Improved code summarization via a graph neural network](https://arxiv.org/pdf/2004.02843.pdf)

* #### ICLR-18
[learning to represent programs with graphs](https://openreview.net/pdf?id=BJOFETxR-)

* #### ICLR-19
[Structured Neural Summarization](https://openreview.net/pdf?id=H1ersoRqtm)

- ### Graph2Seq
* #### ArXiv-20
[Improved code summarization via a graph neural network](https://arxiv.org/pdf/2004.02843.pdf)

* #### ICLR-18
[learning to represent programs with graphs](https://openreview.net/pdf?id=BJOFETxR-)

* #### ICLR-19
[Structured Neural Summarization](https://openreview.net/pdf?id=H1ersoRqtm)

- ## Event Detection
- ### Position
* #### RANLP-17
[Graph-based Event Extraction from Twitter](https://www.aclweb.org/anthology/R17-1031/)

- ### Co-occurrence
* #### RANLP-17
[Graph-based Event Extraction from Twitter](https://www.aclweb.org/anthology/R17-1031/)

- ### Dependency
* #### AAAI-18
[Graph Convolutional Networks with Argument-Aware Pooling for Event Detection](https://nyuscholars.nyu.edu/en/publications/graph-convolutional-networks-with-argument-aware-pooling-for-even)

[Graph Convolutional Networks with Argument-Aware Pooling for Event Detection](https://aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16329/16155)

* #### EMNLP-19
[Event Detection with Multi-Order Graph Convolution and Aggregated Attention](https://www.aclweb.org/anthology/D19-1582/)

* #### EMNLP-20
[Edge-Enhanced Graph Convolution Networks for Event Detection with Syntactic Relation](https://www.aclweb.org/anthology/2020.findings-emnlp.211/)

* #### EMNLP-18
[Jointly Multiple Events Extraction via Attention-based Graph Information Aggregation](https://www.aclweb.org/anthology/D18-1156/)

- ### GNN for Directed Graphs
* #### ACL-19
[Encoding Social Information with Graph Convolutional Networks for Political Perspective Detection in News Media](https://www.aclweb.org/anthology/P19-1247.pdf)

* #### AAAI-18
[Graph Convolutional Networks with Argument-Aware Pooling for Event Detection](https://nyuscholars.nyu.edu/en/publications/graph-convolutional-networks-with-argument-aware-pooling-for-even)

[Graph Convolutional Networks with Argument-Aware Pooling for Event Detection](https://aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16329/16155)

* #### EMNLP-19
[Event Detection with Multi-Order Graph Convolution and Aggregated Attention](https://www.aclweb.org/anthology/D19-1582/)

* #### EMNLP-20
[Edge-Enhanced Graph Convolution Networks for Event Detection with Syntactic Relation](https://www.aclweb.org/anthology/2020.findings-emnlp.211/)

[Event Detection: Gate Diversity and Syntactic Importance Scores for Graph Convolution Neural Networks](https://www.aclweb.org/anthology/2020.emnlp-main.583/)

* #### EMNLP-18
[Jointly Multiple Events Extraction via Attention-based Graph Information Aggregation](https://www.aclweb.org/anthology/D18-1156/)

- ### App-driven
* #### ACL-19
[Encoding Social Information with Graph Convolutional Networks for Political Perspective Detection in News Media](https://www.aclweb.org/anthology/P19-1247.pdf)

- ### Knowledge
* #### EMNLP-20
[Event Detection: Gate Diversity and Syntactic Importance Scores for Graph Convolution Neural Networks](https://www.aclweb.org/anthology/2020.emnlp-main.583/)

- ## Natural Language Inference
- ### Knowledge
* #### AAAI-19
[Improving Natural Language Inference Using External Knowledgein the Science Questions Domain](https://ojs.aaai.org//index.php/AAAI/article/view/4705)

* #### AAAI-20
[Infusing Knowledge into the Textual Entailment Task Using Graph Convolutional Networks](https://www.semanticscholar.org/paper/Infusing-Knowledge-into-the-Textual-Entailment-Task-Kapanipathi-Thost/4f8e1a4247ce06a15760fc2692c6849601d41b6f)

* #### EMNLP-19
[KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning](https://www.aclweb.org/anthology/D19-1282/)

- ## Semantic Role Labeling
- ### Dependency
* #### ArXiv-20
[Cross-Lingual Semantic Role Labeling With Model Transfer](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9165903)

[Semantic Role Labeling with Heterogeneous Syntactic Knowledge](https://www.aclweb.org/anthology/2020.coling-main.266.pdf)

* #### ACL-20
[Syntax-Aware Opinion Role Labeling with Dependency Graph Convolutional Networks](https://www.aclweb.org/anthology/2020.acl-main.297.pdf)

* #### EMNLP-17
[Encoding Sentences with Graph Convolutional Networks](https://www.aclweb.org/anthology/D17-1159.pdf)

* #### EMNLP-18
[A Unified Syntax-aware Framework for Semantic Role Labeling](https://www.aclweb.org/anthology/D18-1262.pdf)

- ### GNN for Directed Graphs
* #### ArXiv-20
[Semantic Role Labeling with Heterogeneous Syntactic Knowledge](https://www.aclweb.org/anthology/2020.coling-main.266.pdf)

* #### ACL-20
[Syntax-Aware Opinion Role Labeling with Dependency Graph Convolutional Networks](https://www.aclweb.org/anthology/2020.acl-main.297.pdf)

* #### EMNLP-20
[Graph Convolutions over Constituent Trees for Syntax-Aware Semantic Role Labeling](https://www.aclweb.org/anthology/2020.emnlp-main.322.pdf)

* #### EMNLP-17
[Encoding Sentences with Graph Convolutional Networks](https://www.aclweb.org/anthology/D17-1159.pdf)

* #### EMNLP-18
[A Unified Syntax-aware Framework for Semantic Role Labeling](https://www.aclweb.org/anthology/D18-1262.pdf)

- ### GNN for Heterogeneous Graphs
* #### ArXiv-20
[Cross-Lingual Semantic Role Labeling With Model Transfer](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9165903)

[Semantic Role Labeling with Heterogeneous Syntactic Knowledge](https://www.aclweb.org/anthology/2020.coling-main.266.pdf)

* #### EMNLP-20
[Graph Convolutions over Constituent Trees for Syntax-Aware Semantic Role Labeling](https://www.aclweb.org/anthology/2020.emnlp-main.322.pdf)

* #### EMNLP-17
[Encoding Sentences with Graph Convolutional Networks](https://www.aclweb.org/anthology/D17-1159.pdf)

* #### EMNLP-18
[A Unified Syntax-aware Framework for Semantic Role Labeling](https://www.aclweb.org/anthology/D18-1262.pdf)

- ### Constituency
* #### EMNLP-20
[Graph Convolutions over Constituent Trees for Syntax-Aware Semantic Role Labeling](https://www.aclweb.org/anthology/2020.emnlp-main.322.pdf)

- ### GNN for Undirected Graphs
* #### ArXiv-20
[Cross-Lingual Semantic Role Labeling With Model Transfer](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9165903)

- ## Fact Verification
- ### App-driven
* #### ACL-19
[GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification](https://www.aclweb.org/anthology/P19-1085.pdf)

- ### GNN for Undirected Graphs
* #### ACL-19
[GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification](https://www.aclweb.org/anthology/P19-1085.pdf)

- ## AMR Parsing
- ### Graph2Graph
* #### ACL-20
[AMR Parsing with Latent Structural Information](https://www.aclweb.org/anthology/2020.acl-main.397/)

* #### EMNLP-20
[Online Back-Parsing for AMR-to-Text Generation](https://www.aclweb.org/anthology/2020.emnlp-main.92/)

- ### Dependency
* #### ACL-20
[AMR Parsing with Latent Structural Information](https://www.aclweb.org/anthology/2020.acl-main.397/)

- ### GNN for Directed Graphs
* #### ACL-20
[AMR Parsing with Latent Structural Information](https://www.aclweb.org/anthology/2020.acl-main.397/)

* #### EMNLP-20
[Online Back-Parsing for AMR-to-Text Generation](https://www.aclweb.org/anthology/2020.emnlp-main.92/)

- ### App-driven
* #### ACL-20
[AMR Parsing via Graph_x001C_Sequence Iterative Inference(to be deleted)](https://www.aclweb.org/anthology/2020.acl-main.119/)

* #### ACL-19
[AMR Parsing as Sequence-to-Graph Transduction(to be deleted)](https://www.aclweb.org/anthology/P19-1009/)

* #### ACL-18
[AMR Parsing as Graph Prediction with Latent Alignment(to be deleted)](https://www.aclweb.org/anthology/P18-1037/)

- ### AMR
* #### EMNLP-20
[Online Back-Parsing for AMR-to-Text Generation](https://www.aclweb.org/anthology/2020.emnlp-main.92/)

- ### Graph2Seq
* #### EMNLP-20
[Online Back-Parsing for AMR-to-Text Generation](https://www.aclweb.org/anthology/2020.emnlp-main.92/)

- ## Sentiment Analysis
- ### Dependency
* #### ACL-20
[Dependency Graph Enhanced Dual-transformer Structure for Aspect-based Sentiment Classification](https://www.aclweb.org/anthology/2020.acl-main.588/)

[Relational Graph Attention Network for Aspect-based Sentiment Analysis](https://www.aclweb.org/anthology/2020.acl-main.295)

* #### EMNLP-19
[Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks](https://www.aclweb.org/anthology/D19-1549)

[Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks](https://www.aclweb.org/anthology/D19-1464)

* #### EMNLP-20
[Improving Aspect-based Sentiment Analysis with Gated Graph Convolutional Networks and Syntax-based Regulation](https://www.aclweb.org/anthology/2020.findings-emnlp.407)

- ### GNN for Directed Graphs
* #### ACL-20
[KinGDOM: Knowledge-Guided DOMain Adaptation for Sentiment Analysis](https://www.aclweb.org/anthology/2020.acl-main.292/)

[Aspect Sentiment Classification with Document-level Sentiment Preference Modeling](https://www.aclweb.org/anthology/2020.acl-main.338/)

[Dependency Graph Enhanced Dual-transformer Structure for Aspect-based Sentiment Classification](https://www.aclweb.org/anthology/2020.acl-main.588/)

[Relational Graph Attention Network for Aspect-based Sentiment Analysis](https://www.aclweb.org/anthology/2020.acl-main.295)

* #### EMNLP-19
[Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks](https://www.aclweb.org/anthology/D19-1549)

- ### GNN for undirected graphs
* #### EMNLP-20
[Convolution over Hierarchical Syntactic and Lexical Graphs for Aspect Level Sentiment Analysis](https://www.aclweb.org/anthology/2020.emnlp-main.286)

- ### Similarity
* #### ACL-20
[Aspect Sentiment Classification with Document-level Sentiment Preference Modeling](https://www.aclweb.org/anthology/2020.acl-main.338/)

* #### EMNLP-20
[Convolution over Hierarchical Syntactic and Lexical Graphs for Aspect Level Sentiment Analysis](https://www.aclweb.org/anthology/2020.emnlp-main.286/)

[Convolution over Hierarchical Syntactic and Lexical Graphs for Aspect Level Sentiment Analysis](https://www.aclweb.org/anthology/2020.emnlp-main.286)

- ### GNN for Undirected Graphs
* #### EMNLP-19
[Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks](https://www.aclweb.org/anthology/D19-1464)

* #### EMNLP-20
[Improving Aspect-based Sentiment Analysis with Gated Graph Convolutional Networks and Syntax-based Regulation](https://www.aclweb.org/anthology/2020.findings-emnlp.407)

- ### GNN on Undirected Graphs
* #### EMNLP-20
[Convolution over Hierarchical Syntactic and Lexical Graphs for Aspect Level Sentiment Analysis](https://www.aclweb.org/anthology/2020.emnlp-main.286/)

- ### Knowledge
* #### ACL-20
[KinGDOM: Knowledge-Guided DOMain Adaptation for Sentiment Analysis](https://www.aclweb.org/anthology/2020.acl-main.292/)

- ## Semantic Parsing
- ### Dependency
* #### EMNLP-20
[Graph-to-Tree Neural Networksfor Learning Structured Input-Output Translationwith Applications to Semantic Parsing and Math Word Problem](https://www.aclweb.org/anthology/2020.findings-emnlp.255/)

* #### EMNLP-18
[Exploiting Rich Syntactic Information for Semantic Parsingwith Graph-to-Sequence Mode](https://www.aclweb.org/anthology/D18-1110/)

- ### GNN for Directed Graphs
* #### ACL-19
[Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing](https://www.aclweb.org/anthology/P19-1448/)

* #### EMNLP-20
[Graph-to-Tree Neural Networksfor Learning Structured Input-Output Translationwith Applications to Semantic Parsing and Math Word Problem](https://www.aclweb.org/anthology/2020.findings-emnlp.255/)

- ### App-driven
* #### AAAI-20
[Graph-Based Transformer with Cross-Candidate Verification for Semantic Parsing](https://ojs.aaai.org//index.php/AAAI/article/view/6408)

* #### ACL-19
[Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing](https://www.aclweb.org/anthology/P19-1448/)

* #### EMNLP-19
[Global Reasoning over Database Structures for Text-to-SQL Parsing](https://www.aclweb.org/anthology/D19-1378/)

- ### GNN for Heterogeneous Graphs
* #### EMNLP-20
[Graph-to-Tree Neural Networksfor Learning Structured Input-Output Translationwith Applications to Semantic Parsing and Math Word Problem](https://www.aclweb.org/anthology/2020.findings-emnlp.255/)

* #### EMNLP-18
[Exploiting Rich Syntactic Information for Semantic Parsingwith Graph-to-Sequence Mode](https://www.aclweb.org/anthology/D18-1110/)

- ### Constituency
* #### EMNLP-20
[Graph-to-Tree Neural Networksfor Learning Structured Input-Output Translationwith Applications to Semantic Parsing and Math Word Problem](https://www.aclweb.org/anthology/2020.findings-emnlp.255/)

* #### EMNLP-18
[Exploiting Rich Syntactic Information for Semantic Parsingwith Graph-to-Sequence Mode](https://www.aclweb.org/anthology/D18-1110/)

- ### Graph2Seq
* #### EMNLP-18
[Exploiting Rich Syntactic Information for Semantic Parsingwith Graph-to-Sequence Mode](https://www.aclweb.org/anthology/D18-1110/)

- ### GNN for Undirected Graphs
* #### EMNLP-18
[Exploiting Rich Syntactic Information for Semantic Parsingwith Graph-to-Sequence Mode](https://www.aclweb.org/anthology/D18-1110/)

- ### Graph2Tree
* #### EMNLP-20
[Graph-to-Tree Neural Networksfor Learning Structured Input-Output Translationwith Applications to Semantic Parsing and Math Word Problem](https://www.aclweb.org/anthology/2020.findings-emnlp.255/)

- ## Knowledge Graph Embedding
- ### GNN for Directed Graphs
* #### ACL-19
[Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs](https://www.aclweb.org/anthology/P19-1466.pdf)

- ### GNN for Heterogeneous Graphs
* #### ACL-20
[ReInceptionE: Relation-Aware Inception Network with Joint Local-Global Structural Information for Knowledge Graph Embedding](https://www.aclweb.org/anthology/2020.acl-main.526.pdf)

* #### EMNLP-19
[CaRe: Open Knowledge Graph Embeddings](https://www.aclweb.org/anthology/D19-1036.pdf)

* #### IJCAI-19
[A Vectorized Relational Graph Convolutional Network for Multi-Relational Network Alignment](https://www.ijcai.org/Proceedings/2019/0574.pdf)

* #### NAACL-19
[Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks](https://www.aclweb.org/anthology/N19-1306.pdf)

- ### GNN for Undirected Graphs
* #### ACL-19
[A2N: Attending to Neighbors for Knowledge Graph Inference](https://www.aclweb.org/anthology/P19-1431.pdf)

- ### Knowledge
* #### AAAI-19
[Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding](https://ojs.aaai.org//index.php/AAAI/article/view/4698)

* #### ACL-20
[ReInceptionE: Relation-Aware Inception Network with Joint Local-Global Structural Information for Knowledge Graph Embedding](https://www.aclweb.org/anthology/2020.acl-main.526.pdf)

* #### ACL-19
[Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs](https://www.aclweb.org/anthology/P19-1466.pdf)

[A2N: Attending to Neighbors for Knowledge Graph Inference](https://www.aclweb.org/anthology/P19-1431.pdf)

* #### EMNLP-19
[CaRe: Open Knowledge Graph Embeddings](https://www.aclweb.org/anthology/D19-1036.pdf)

* #### IJCAI-19
[A Vectorized Relational Graph Convolutional Network for Multi-Relational Network Alignment](https://www.ijcai.org/Proceedings/2019/0574.pdf)

* #### NAACL-19
[Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks](https://www.aclweb.org/anthology/N19-1306.pdf)

- ## Knowledge Base Completion
- ### GNN for Directed Graphs
* #### ACL-19
[Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs](https://www.aclweb.org/anthology/P19-1466.pdf)

[Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs](https://www.aclweb.org/anthology/P19-1466.pdf)

* #### ICLR-20
[DYNAMICALLY PRUNED MESSAGE PASSING NETWORKS FOR LARGE-SCALE KNOWLEDGE GRAPH
REASONING](https://openreview.net/pdf?id=rkeuAhVKvB)

- ### GNN for Heterogeneous Graphs
* #### AAAI-20
[Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion](https://ojs.aaai.org//index.php/AAAI/article/view/6508)

* #### ESWC 2018
[Modeling Relational Data with Graph Convolutional Networks](https://link.springer.com/chapter/10.1007/978-3-319-93417-4_38)

* #### ACL-19
[Multi-Channel Graph Neural Network for Entity Alignment](https://www.aclweb.org/anthology/P19-1140.pdf)

* #### ICML-20
[Inductive Relation Prediction by Subgraph Reasoning](http://proceedings.mlr.press/v119/teru20a/teru20a.pdf)

* #### EMNLP-20
[TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion](https://www.aclweb.org/anthology/2020.emnlp-main.462.pdf)

* #### IJCAI-19
[Robust Embedding with Multi-Level Structures for Link Prediction](https://www.ijcai.org/Proceedings/2019/0728.pdf)

- ### GNN for Undirected Graphs
* #### AAAI-19
[End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion](https://ojs.aaai.org//index.php/AAAI/article/view/4164)

* #### AAAI-20
[Commonsense Knowledge Base Completion with Structural and Semantic Context](https://ojs.aaai.org/index.php/AAAI/article/download/5684/5540)

* #### ACL-19
[A2N: Attending to Neighbors for Knowledge Graph Inference](https://www.aclweb.org/anthology/P19-1431.pdf)

* #### ICML-20
[Inductive Relation Prediction by Subgraph Reasoning](http://proceedings.mlr.press/v119/teru20a/teru20a.pdf)

* #### EMNLP-19
[Incorporating Graph Attention Mechanism into Knowledge Graph Reasoning Based on Deep Reinforcement Learning](https://www.aclweb.org/anthology/D19-1264.pdf)

- ### Knowledge
* #### AAAI-19
[End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion](https://ojs.aaai.org//index.php/AAAI/article/view/4164)

* #### AAAI-20
[Commonsense Knowledge Base Completion with Structural and Semantic Context](https://ojs.aaai.org/index.php/AAAI/article/download/5684/5540)

[Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion](https://ojs.aaai.org//index.php/AAAI/article/view/6508)

* #### ESWC 2018
[Modeling Relational Data with Graph Convolutional Networks](https://link.springer.com/chapter/10.1007/978-3-319-93417-4_38)

* #### ACL-19
[Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs](https://www.aclweb.org/anthology/P19-1466.pdf)

[A2N: Attending to Neighbors for Knowledge Graph Inference](https://www.aclweb.org/anthology/P19-1431.pdf)

[Multi-Channel Graph Neural Network for Entity Alignment](https://www.aclweb.org/anthology/P19-1140.pdf)

[Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs](https://www.aclweb.org/anthology/P19-1466.pdf)

* #### ICML-20
[Inductive Relation Prediction by Subgraph Reasoning](http://proceedings.mlr.press/v119/teru20a/teru20a.pdf)

[Inductive Relation Prediction by Subgraph Reasoning](http://proceedings.mlr.press/v119/teru20a/teru20a.pdf)

* #### EMNLP-19
[Incorporating Graph Attention Mechanism into Knowledge Graph Reasoning Based on Deep Reinforcement Learning](https://www.aclweb.org/anthology/D19-1264.pdf)

* #### EMNLP-20
[TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion](https://www.aclweb.org/anthology/2020.emnlp-main.462.pdf)

* #### IJCAI-19
[Robust Embedding with Multi-Level Structures for Link Prediction](https://www.ijcai.org/Proceedings/2019/0728.pdf)

* #### ICLR-20
[DYNAMICALLY PRUNED MESSAGE PASSING NETWORKS FOR LARGE-SCALE KNOWLEDGE GRAPH
REASONING](https://openreview.net/pdf?id=rkeuAhVKvB)

- ## Summarization
- ### Co-occurrence
* #### EMNLP-20
[Neural Extractive Summarization with Hierarchical Attentive Heterogeneous Graph Network](https://www.aclweb.org/anthology/2020.emnlp-main.295/)

- ### Coreference
* #### ACL-20
[Discourse-Aware Neural Extractive Text Summarization](https://www.aclweb.org/anthology/2020.acl-main.451.pdf)

- ### Dependency
* #### AAAI-20
[SemSUM: Semantic Dependency Guided Neural Abstractive Summarization](https://ojs.aaai.org//index.php/AAAI/article/view/6312)

- ### GNN for Directed Graphs
* #### AAAI-20
[SemSUM: Semantic Dependency Guided Neural Abstractive Summarization](https://ojs.aaai.org//index.php/AAAI/article/view/6312)

* #### COLING-20
[Improving Abstractive Dialogue Summarization with Graph Structures and Topic Words](https://www.aclweb.org/anthology/2020.coling-main.39/)

* #### ACL-20
[Discourse-Aware Neural Extractive Text Summarization](https://www.aclweb.org/anthology/2020.acl-main.451.pdf)

[Discourse-Aware Neural Extractive Text Summarization](https://www.aclweb.org/anthology/2020.acl-main.451.pdf)

[Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward](https://www.aclweb.org/anthology/2020.acl-main.457.pdf)

[Leveraging Graph to Improve Abstractive Multi-Document Summarization](https://www.aclweb.org/anthology/2020.acl-main.555.pdf)

* #### EMNLP-20
[Neural Extractive Summarization with Hierarchical Attentive Heterogeneous Graph Network](https://www.aclweb.org/anthology/2020.emnlp-main.295/)

[Summarizing Chinese Medical Answer with Graph Convolution Networks and Question-focused Dual Attention](https://www.aclweb.org/anthology/2020.findings-emnlp.2/)

* #### ACL-17
[Abstractive document summarization with a graph-based attentional neural model](https://www.aclweb.org/anthology/P17-1108/)

- ### AMR
* #### COLING-18
[Abstract Meaning Representation for Multi-Document Summarization](https://www.aclweb.org/anthology/C18-1101.pdf)

- ### Discourse
* #### ACL-20
[Discourse-Aware Neural Extractive Text Summarization](https://www.aclweb.org/anthology/2020.acl-main.451.pdf)

[Discourse-Aware Neural Extractive Text Summarization](https://www.aclweb.org/anthology/2020.acl-main.451.pdf)

[Leveraging Graph to Improve Abstractive Multi-Document Summarization](https://www.aclweb.org/anthology/2020.acl-main.555.pdf)

* #### COLING-17
[Graph-based Neural Multi-Document Summarization](https://www.aclweb.org/anthology/K17-1045/)

* #### ACL-17
[Abstractive document summarization with a graph-based attentional neural model](https://www.aclweb.org/anthology/P17-1108/)

- ### GNN for Heterogeneous Graphs
* #### ACL-20
[Heterogeneous Graph Neural Networks for Extractive Document Summarization](https://www.aclweb.org/anthology/2020.acl-main.553.pdf)

- ### Node Embedding Based
* #### COLING-20
[Enhancing Extractive Text Summarization with Topic-Aware Graph Neural Networks](https://www.aclweb.org/anthology/2020.coling-main.468.pdf)

- ### Similarity
* #### COLING-20
[Improving Abstractive Dialogue Summarization with Graph Structures and Topic Words](https://www.aclweb.org/anthology/2020.coling-main.39/)

* #### ACL-20
[Leveraging Graph to Improve Abstractive Multi-Document Summarization](https://www.aclweb.org/anthology/2020.acl-main.555.pdf)

[Heterogeneous Graph Neural Networks for Extractive Document Summarization](https://www.aclweb.org/anthology/2020.acl-main.553.pdf)

* #### EMNLP-20
[Neural Extractive Summarization with Hierarchical Attentive Heterogeneous Graph Network](https://www.aclweb.org/anthology/2020.emnlp-main.295/)

[Summarizing Chinese Medical Answer with Graph Convolution Networks and Question-focused Dual Attention](https://www.aclweb.org/anthology/2020.findings-emnlp.2/)

* #### COLING-17
[Graph-based Neural Multi-Document Summarization](https://www.aclweb.org/anthology/K17-1045/)

- ### Graph2Seq
* #### COLING-20
[Improving Abstractive Dialogue Summarization with Graph Structures and Topic Words](https://www.aclweb.org/anthology/2020.coling-main.39/)

[Enhancing Extractive Text Summarization with Topic-Aware Graph Neural Networks](https://www.aclweb.org/anthology/2020.coling-main.468.pdf)

* #### ACL-20
[Discourse-Aware Neural Extractive Text Summarization](https://www.aclweb.org/anthology/2020.acl-main.451.pdf)

[Discourse-Aware Neural Extractive Text Summarization](https://www.aclweb.org/anthology/2020.acl-main.451.pdf)

[Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward](https://www.aclweb.org/anthology/2020.acl-main.457.pdf)

[Leveraging Graph to Improve Abstractive Multi-Document Summarization](https://www.aclweb.org/anthology/2020.acl-main.555.pdf)

[Heterogeneous Graph Neural Networks for Extractive Document Summarization](https://www.aclweb.org/anthology/2020.acl-main.553.pdf)

* #### EMNLP-20
[Neural Extractive Summarization with Hierarchical Attentive Heterogeneous Graph Network](https://www.aclweb.org/anthology/2020.emnlp-main.295/)

[Summarizing Chinese Medical Answer with Graph Convolution Networks and Question-focused Dual Attention](https://www.aclweb.org/anthology/2020.findings-emnlp.2/)

* #### COLING-17
[Graph-based Neural Multi-Document Summarization](https://www.aclweb.org/anthology/K17-1045/)

* #### COLING-18
[Abstract Meaning Representation for Multi-Document Summarization](https://www.aclweb.org/anthology/C18-1101.pdf)

* #### ACL-17
[Abstractive document summarization with a graph-based attentional neural model](https://www.aclweb.org/anthology/P17-1108/)

- ### GNN for Undirected Graphs
* #### COLING-17
[Graph-based Neural Multi-Document Summarization](https://www.aclweb.org/anthology/K17-1045/)

- ### IE
* #### ACL-20
[Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward](https://www.aclweb.org/anthology/2020.acl-main.457.pdf)

- ### Topic
* #### ACL-20
[Leveraging Graph to Improve Abstractive Multi-Document Summarization](https://www.aclweb.org/anthology/2020.acl-main.555.pdf)

- ## Text Classification
- ### Coreference
* #### ACL-20
[Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks](https://www.aclweb.org/anthology/2020.acl-main.31.pdf)

- ### App-driven
* #### AAAI-19
[Graph Convolutional Networks for Text Classification](https://ojs.aaai.org//index.php/AAAI/article/view/4725)

* #### AAAI-20
[Tensor Graph Convolutional Networks for Text Classification](https://ojs.aaai.org//index.php/AAAI/article/view/6359)

* #### EMNLP-19
[Text Level Graph Neural Network for Text Classification](https://www.aclweb.org/anthology/D19-1345/)

[Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification](https://www.aclweb.org/anthology/D19-1488/)

- ### GNN for Heterogeneous Graphs
* #### AAAI-20
[Tensor Graph Convolutional Networks for Text Classification](https://ojs.aaai.org//index.php/AAAI/article/view/6359)

* #### EMNLP-19
[Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification](https://www.aclweb.org/anthology/D19-1488/)

- ### GNN for Undirected Graphs
* #### AAAI-19
[Graph Convolutional Networks for Text Classification](https://ojs.aaai.org//index.php/AAAI/article/view/4725)

* #### ACL-20
[Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks](https://www.aclweb.org/anthology/2020.acl-main.31.pdf)

* #### EMNLP-19
[Text Level Graph Neural Network for Text Classification](https://www.aclweb.org/anthology/D19-1345/)

- ## Relation Extraction
- ### Node Embedding Based Refined
* #### NAACL-19
[A General Framework for Information Extraction using Dynamic Span Graphs](https://www.aclweb.org/anthology/N19-1308.pdf)

- ### Co-occurrence
* #### EMNLP-19
[Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs](https://www.aclweb.org/anthology/D19-1498/)

- ### Document
* #### EMNLP-19
[Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs](https://www.aclweb.org/anthology/D19-1498/)

- ### Coreference
* #### ACL-19
[Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network](https://www.aclweb.org/anthology/P19-1423/)

* #### NAACL-19
[A General Framework for Information Extraction using Dynamic Span Graphs](https://www.aclweb.org/anthology/N19-1308.pdf)

- ### Dependency
* #### ACL-19
[GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction](https://www.aclweb.org/anthology/P19-1136.pdf)

[Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network](https://www.aclweb.org/anthology/P19-1423/)

[Attention Guided Graph Convolutional Networks for Relation Extraction](https://www.aclweb.org/anthology/P19-1024/)

[Attention Guided Graph Convolutional Networks for Relation Extraction](https://www.aclweb.org/anthology/P19-1024.pdf)

* #### NAACL-19
[GraphIE: A Graph-Based Framework for Information Extraction](https://www.aclweb.org/anthology/N19-1082/)

* #### EMNLP-18
[Graph Convolution over Pruned Dependency Trees Improves Relation Extraction](https://www.aclweb.org/anthology/D18-1244.pdf)

[RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information](https://www.aclweb.org/anthology/D18-1157/)

[N-ary Relation Extraction using Graph State LSTM](https://www.aclweb.org/anthology/D18-1246.pdf)

- ### GNN for Directed Graphs
* #### ACL-20
[Structural Information Preserving for Graph-to-Text Generation](https://www.aclweb.org/anthology/2020.acl-main.712/)

* #### ACL-19
[Attention Guided Graph Convolutional Networks for Relation Extraction](https://www.aclweb.org/anthology/P19-1024.pdf)

* #### EMNLP-18
[Graph Convolution over Pruned Dependency Trees Improves Relation Extraction](https://www.aclweb.org/anthology/D18-1244.pdf)

[RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information](https://www.aclweb.org/anthology/D18-1157/)

[N-ary Relation Extraction using Graph State LSTM](https://www.aclweb.org/anthology/D18-1246.pdf)

- ### App-driven
* #### ACL-20
[Transition-based Directed Graph Construction for Emotion-Cause Pair Extraction](https://www.aclweb.org/anthology/2020.acl-main.342.pdf)

* #### ICML-20
[Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs](http://proceedings.mlr.press/v119/qu20a/qu20a.pdf)

* #### EMNLP-20
[Double Graph Based Reasoning for Document-level Relation Extraction](https://www.aclweb.org/anthology/2020.emnlp-main.127.pdf)

- ### AMR
* #### ACL-20
[Structural Information Preserving for Graph-to-Text Generation](https://www.aclweb.org/anthology/2020.acl-main.712/)

- ### GNN for Heterogeneous Graphs
* #### ACL-19
[GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction](https://www.aclweb.org/anthology/P19-1136.pdf)

[Joint Type Inference on Entities and Relations via Graph Convolutional Networks](https://www.aclweb.org/anthology/P19-1131/)

[Graph Neural Networks with Generated Parameters for Relation Extraction](https://www.aclweb.org/anthology/P19-1128/)

* #### EMNLP-19
[Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs](https://www.aclweb.org/anthology/D19-1498/)

* #### EMNLP-20
[Double Graph Based Reasoning for Document-level Relation Extraction](https://www.aclweb.org/anthology/2020.emnlp-main.127.pdf)

* #### NAACL-19
[Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks](https://www.aclweb.org/anthology/N19-1306.pdf)

- ### Graph2Seq
* #### ACL-20
[Structural Information Preserving for Graph-to-Text Generation](https://www.aclweb.org/anthology/2020.acl-main.712/)

- ### GNN for Undirected Graphs
* #### ACL-19
[Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network](https://www.aclweb.org/anthology/P19-1423/)

[Attention Guided Graph Convolutional Networks for Relation Extraction](https://www.aclweb.org/anthology/P19-1024/)

* #### ICML-20
[Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs](http://proceedings.mlr.press/v119/qu20a/qu20a.pdf)

* #### NAACL-19
[GraphIE: A Graph-Based Framework for Information Extraction](https://www.aclweb.org/anthology/N19-1082/)

- ### IE
* #### EMNLP-18
[RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information](https://www.aclweb.org/anthology/D18-1157/)

- ### Knowledge
* #### ACL-20
[Structural Information Preserving for Graph-to-Text Generation](https://www.aclweb.org/anthology/2020.acl-main.712/)

* #### NAACL-19
[Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks](https://www.aclweb.org/anthology/N19-1306.pdf)

* #### EMNLP-18
[RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information](https://www.aclweb.org/anthology/D18-1157/)

- ## Machine Reading Comprehension
- ### Co-occurrence
* #### ACL-19
[Dynamically Fused Graph Network for Multi-hop Reasoning](https://www.aclweb.org/anthology/P19-1617/)

- ### Coreference
* #### NAACL-19
[Question Answering by Reasoning Across Documents with Graph Convolutional Networks](https://www.aclweb.org/anthology/N19-1240/)

- ### GNN for Directed Graphs
* #### ACL-20
[Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings](https://www.aclweb.org/anthology/2020.acl-main.412/)

[Document Modeling with Graph Attention Networks for Multi-grained Machine Reading Comprehension](https://www.aclweb.org/anthology/2020.acl-main.599/)

* #### ACL-19
[Dynamically Fused Graph Network for Multi-hop Reasoning](https://www.aclweb.org/anthology/P19-1617/)

- ### App-driven
* #### ACL-20
[Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks](https://www.aclweb.org/anthology/D19-5306/)

[Document Modeling with Graph Attention Networks for Multi-grained Machine Reading Comprehension](https://www.aclweb.org/anthology/2020.acl-main.599/)

* #### ACL-19
[Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs](https://www.aclweb.org/anthology/P19-1260/)

[Cognitive Graph for Multi-Hop Reading Comprehension at Scale](https://www.aclweb.org/anthology/P19-1259/)

* #### EMNLP-19
[NumNet: Machine Reading Comprehension with Numerical Reasoning](https://www.aclweb.org/anthology/D19-1251/)

* #### EMNLP-20
[Hierarchical Graph Network for Multi-hop Question Answering](https://www.aclweb.org/anthology/2020.emnlp-main.710/)

[SRLGRN: Semantic Role Labeling Graph Reasoning Network](https://www.aclweb.org/anthology/2020.emnlp-main.714.pdf)

* #### IJCAI-20
[Multi-hop Reading Comprehension across Documents with Path-based Graph Convolutional Network](https://www.ijcai.org/Proceedings/2020/540)

- ### GNN for Heterogeneous Graphs
* #### ACL-19
[Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs](https://www.aclweb.org/anthology/P19-1260/)

* #### EMNLP-19
[NumNet: Machine Reading Comprehension with Numerical Reasoning](https://www.aclweb.org/anthology/D19-1251/)

* #### EMNLP-20
[SRLGRN: Semantic Role Labeling Graph Reasoning Network](https://www.aclweb.org/anthology/2020.emnlp-main.714.pdf)

* #### NAACL-19
[Question Answering by Reasoning Across Documents with Graph Convolutional Networks](https://www.aclweb.org/anthology/N19-1240/)

* #### IJCAI-20
[Multi-hop Reading Comprehension across Documents with Path-based Graph Convolutional Network](https://www.ijcai.org/Proceedings/2020/540)

- ### Node Embedding Based
* #### IJCAI-20
[GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension](https://www.ijcai.org/Proceedings/2020/171)

- ### Graph2Seq
* #### ACL-20
[Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings](https://www.aclweb.org/anthology/2020.acl-main.412/)

[Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks](https://www.aclweb.org/anthology/D19-5306/)

* #### ACL-19
[Dynamically Fused Graph Network for Multi-hop Reasoning](https://www.aclweb.org/anthology/P19-1617/)

- ### GNN for Undirected Graphs
* #### ACL-20
[Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks](https://www.aclweb.org/anthology/D19-5306/)

* #### ACL-19
[Cognitive Graph for Multi-Hop Reading Comprehension at Scale](https://www.aclweb.org/anthology/P19-1259/)

* #### EMNLP-20
[Hierarchical Graph Network for Multi-hop Question Answering](https://www.aclweb.org/anthology/2020.emnlp-main.710/)

[SRLGRN: Semantic Role Labeling Graph Reasoning Network](https://www.aclweb.org/anthology/2020.emnlp-main.714.pdf)

* #### NAACL-19
[BAG: Bi-directional Attention Entity Graph Convolutional Network for Multi-hop Reasoning Question Answering](https://www.aclweb.org/anthology/N19-1032/)

* #### IJCAI-20
[GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension](https://www.ijcai.org/Proceedings/2020/171)

- ### IE
* #### EMNLP-20
[SRLGRN: Semantic Role Labeling Graph Reasoning Network](https://www.aclweb.org/anthology/2020.emnlp-main.714.pdf)

* #### NAACL-19
[BAG: Bi-directional Attention Entity Graph Convolutional Network for Multi-hop Reasoning Question Answering](https://www.aclweb.org/anthology/N19-1032/)

- ### Knowledge
* #### ACL-20
[Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings](https://www.aclweb.org/anthology/2020.acl-main.412/)

- ## Community Question Answering
- ### Node Embedding Based
* #### MM-20
[Multi-modal Attentive Graph Pooling Model for Community Question Answer Matching](https://dl.acm.org/doi/pdf/10.1145/3394171.3413711)

* #### MM-19
[Hierarchical Graph Semantic Pooling Network for Multi-modal Community Question Answer Matching](https://dl.acm.org/doi/10.1145/3343031.3350966)

- ### Similarity
* #### MM-20
[Multi-modal Attentive Graph Pooling Model for Community Question Answer Matching](https://dl.acm.org/doi/pdf/10.1145/3394171.3413711)

- ### Graph2Seq
* #### MM-20
[Multi-modal Attentive Graph Pooling Model for Community Question Answer Matching](https://dl.acm.org/doi/pdf/10.1145/3394171.3413711)

* #### MM-19
[Hierarchical Graph Semantic Pooling Network for Multi-modal Community Question Answer Matching](https://dl.acm.org/doi/10.1145/3343031.3350966)

- ### GNN for Undirected Graphs
* #### MM-20
[Multi-modal Attentive Graph Pooling Model for Community Question Answer Matching](https://dl.acm.org/doi/pdf/10.1145/3394171.3413711)

* #### MM-19
[Hierarchical Graph Semantic Pooling Network for Multi-modal Community Question Answer Matching](https://dl.acm.org/doi/10.1145/3343031.3350966)

- ## SQL2Text
- ### GNN for Directed Graphs
* #### ArXiv-18
[Graph2seq: Graph to sequence learning with attention-based neural networks](https://arxiv.org/pdf/1804.00823.pdf)

* #### EMNLP-18
[SQL-to-Text Generation with Graph-to-Sequence Model](https://www.aclweb.org/anthology/D18-1112/)

- ### App-driven
* #### EMNLP-19
[Graph Enhanced Cross-Domain Text-to-SQL Generation](https://www.aclweb.org/anthology/D19-5319/)

* #### ArXiv-18
[Graph2seq: Graph to sequence learning with attention-based neural networks](https://arxiv.org/pdf/1804.00823.pdf)

* #### EMNLP-18
[SQL-to-Text Generation with Graph-to-Sequence Model](https://www.aclweb.org/anthology/D18-1112/)

- ### Graph2Seq
* #### EMNLP-19
[Graph Enhanced Cross-Domain Text-to-SQL Generation](https://www.aclweb.org/anthology/D19-5319/)

* #### ArXiv-18
[Graph2seq: Graph to sequence learning with attention-based neural networks](https://arxiv.org/pdf/1804.00823.pdf)

* #### EMNLP-18
[SQL-to-Text Generation with Graph-to-Sequence Model](https://www.aclweb.org/anthology/D18-1112/)

- ### GNN for Undirected Graphs
* #### EMNLP-19
[Graph Enhanced Cross-Domain Text-to-SQL Generation](https://www.aclweb.org/anthology/D19-5319/)

- ## Machine Translation
- ### Coreference
* #### AAAI-21
[Document Graph for Neural Machine Translation](https://arxiv.org/pdf/2012.03477.pdf)

* #### NAACL-19
[Text Generation from Knowledge Graphs with Graph Transformers](https://www.aclweb.org/anthology/N19-1238/)

- ### Dependency
* #### AAAI-21
[Document Graph for Neural Machine Translation](https://arxiv.org/pdf/2012.03477.pdf)

* #### EMNLP-17
[Graph Convolutional Encoders for Syntax-aware Neural Machine Translation](https://www.aclweb.org/anthology/D17-1209v2.pdf)

* #### ACL-18
[Graph-to-Sequence Learning using Gated Graph Neural Networks](https://www.aclweb.org/anthology/P18-1026/)

* #### NAACL-18
[Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks](https://www.aclweb.org/anthology/N18-2078/)

* #### EACL-17
[Context-Aware Graph Segmentation for Graph-Based Translation](https://www.aclweb.org/anthology/E17-2095.pdf)

- ### GNN for Directed Graphs
* #### AAAI-20
[Graph Transformer for Graph-to-Sequence Learning](https://ojs.aaai.org//index.php/AAAI/article/view/6243)

* #### ACL-19
[Lattice-Based Transformer Encoder for Neural Machine Translation](https://www.aclweb.org/anthology/P19-1298/)

* #### TACL-20
[AMR-To-Text Generation with Graph Transformer](https://www.aclweb.org/anthology/2020.tacl-1.2.pdf)

* #### AAAI-18
[Graph Based Translation Memory for Neural Machine Translation](https://ojs.aaai.org/index.php/AAAI/article/view/4716)

* #### AAAI-21
[Document Graph for Neural Machine Translation](https://arxiv.org/pdf/2012.03477.pdf)

* #### EMNLP-17
[Graph Convolutional Encoders for Syntax-aware Neural Machine Translation](https://www.aclweb.org/anthology/D17-1209v2.pdf)

[Neural Machine Translation with Source-Side Latent Graph Parsing](https://www.aclweb.org/anthology/D17-1012/)

* #### ACL-18
[Graph-to-Sequence Learning using Gated Graph Neural Networks](https://www.aclweb.org/anthology/P18-1026/)

* #### NAACL-19
[Text Generation from Knowledge Graphs with Graph Transformers](https://www.aclweb.org/anthology/N19-1238/)

* #### IJCAI-20
[Knowledge Graphs Enhanced Neural Machine Translation](https://www.ijcai.org/Proceedings/2020/559)

* #### TACL-19
[Semantic neural machine translation using AMR](https://www.aclweb.org/anthology/Q19-1002.pdf)

* #### NAACL-18
[Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks](https://www.aclweb.org/anthology/N18-2078/)

- ### App-driven
* #### ACL-20
[A Novel Graph-based Multi-modal Fusion Encoder for Neural Machine Translation](https://www.aclweb.org/anthology/2020.acl-main.273/)

* #### ACL-19
[Lattice-Based Transformer Encoder for Neural Machine Translation](https://www.aclweb.org/anthology/P19-1298/)

* #### AAAI-18
[Graph Based Translation Memory for Neural Machine Translation](https://ojs.aaai.org/index.php/AAAI/article/view/4716)

- ### AMR
* #### AAAI-20
[Graph Transformer for Graph-to-Sequence Learning](https://ojs.aaai.org//index.php/AAAI/article/view/6243)

* #### ACL-20
[Heterogeneous Graph Transformer for Graph-to-Sequence Learning](https://www.aclweb.org/anthology/2020.acl-main.640.pdf)

* #### TACL-20
[AMR-To-Text Generation with Graph Transformer](https://www.aclweb.org/anthology/2020.tacl-1.2.pdf)

* #### ACL-18
[Graph-to-Sequence Learning using Gated Graph Neural Networks](https://www.aclweb.org/anthology/P18-1026/)

* #### TACL-19
[Semantic neural machine translation using AMR](https://www.aclweb.org/anthology/Q19-1002.pdf)

[Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning](https://www.aclweb.org/anthology/Q19-1019/)

- ### GNN for Heterogeneous Graphs
* #### ACL-20
[Heterogeneous Graph Transformer for Graph-to-Sequence Learning](https://www.aclweb.org/anthology/2020.acl-main.640.pdf)

- ### Node Embedding Based
* #### EMNLP-17
[Neural Machine Translation with Source-Side Latent Graph Parsing](https://www.aclweb.org/anthology/D17-1012/)

- ### Graph2Seq
* #### AAAI-20
[Graph Transformer for Graph-to-Sequence Learning](https://ojs.aaai.org//index.php/AAAI/article/view/6243)

* #### COLING-20
[Knowledge Graph Enhanced Neural Machine Translation via Multi-task Learning on Sub-entity Granularity](https://www.aclweb.org/anthology/2020.coling-main.397/)

* #### ACL-20
[Heterogeneous Graph Transformer for Graph-to-Sequence Learning](https://www.aclweb.org/anthology/2020.acl-main.640.pdf)

[A Novel Graph-based Multi-modal Fusion Encoder for Neural Machine Translation](https://www.aclweb.org/anthology/2020.acl-main.273/)

* #### ACL-19
[Lattice-Based Transformer Encoder for Neural Machine Translation](https://www.aclweb.org/anthology/P19-1298/)

* #### TACL-20
[AMR-To-Text Generation with Graph Transformer](https://www.aclweb.org/anthology/2020.tacl-1.2.pdf)

* #### AAAI-18
[Graph Based Translation Memory for Neural Machine Translation](https://ojs.aaai.org/index.php/AAAI/article/view/4716)

* #### AAAI-21
[Document Graph for Neural Machine Translation](https://arxiv.org/pdf/2012.03477.pdf)

* #### EMNLP-17
[Graph Convolutional Encoders for Syntax-aware Neural Machine Translation](https://www.aclweb.org/anthology/D17-1209v2.pdf)

[Neural Machine Translation with Source-Side Latent Graph Parsing](https://www.aclweb.org/anthology/D17-1012/)

* #### ACL-18
[Graph-to-Sequence Learning using Gated Graph Neural Networks](https://www.aclweb.org/anthology/P18-1026/)

* #### NAACL-19
[Text Generation from Knowledge Graphs with Graph Transformers](https://www.aclweb.org/anthology/N19-1238/)

* #### IJCAI-20
[Knowledge Graphs Enhanced Neural Machine Translation](https://www.ijcai.org/Proceedings/2020/559)

* #### TACL-19
[Semantic neural machine translation using AMR](https://www.aclweb.org/anthology/Q19-1002.pdf)

[Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning](https://www.aclweb.org/anthology/Q19-1019/)

* #### NAACL-18
[Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks](https://www.aclweb.org/anthology/N18-2078/)

* #### EACL-17
[Context-Aware Graph Segmentation for Graph-Based Translation](https://www.aclweb.org/anthology/E17-2095.pdf)

- ### GNN for Undirected Graphs
* #### ACL-20
[A Novel Graph-based Multi-modal Fusion Encoder for Neural Machine Translation](https://www.aclweb.org/anthology/2020.acl-main.273/)

* #### TACL-19
[Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning](https://www.aclweb.org/anthology/Q19-1019/)

- ### Knowledge
* #### COLING-20
[Knowledge Graph Enhanced Neural Machine Translation via Multi-task Learning on Sub-entity Granularity](https://www.aclweb.org/anthology/2020.coling-main.397/)

* #### NAACL-19
[Text Generation from Knowledge Graphs with Graph Transformers](https://www.aclweb.org/anthology/N19-1238/)

* #### IJCAI-20
[Knowledge Graphs Enhanced Neural Machine Translation](https://www.ijcai.org/Proceedings/2020/559)

- ## Knowledge Base Completion/Reasoning
- ### GNN for Directed Graphs
* #### ICLR-20
[DYNAMICALLY PRUNED MESSAGE PASSING NETWORKS FOR LARGE-SCALE KNOWLEDGE GRAPH
REASONING](https://openreview.net/pdf?id=rkeuAhVKvB)

- ### Knowledge
* #### ICLR-20
[DYNAMICALLY PRUNED MESSAGE PASSING NETWORKS FOR LARGE-SCALE KNOWLEDGE GRAPH
REASONING](https://openreview.net/pdf?id=rkeuAhVKvB)

- ## Knowledge Base Question Answering
- ### GNN for Heterogeneous Graphs
* #### EMNLP-20
[Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering](https://www.aclweb.org/anthology/2020.emnlp-main.99/)

* #### COLING-18
[Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering](https://www.aclweb.org/anthology/C18-1280/)

- ### Knowledge
* #### EMNLP-20
[Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering](https://www.aclweb.org/anthology/2020.emnlp-main.99/)

* #### COLING-18
[Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering](https://www.aclweb.org/anthology/C18-1280/)