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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
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This repo is to provide a list of literature regarding Deep Learning on Graphs for NLP
- Host: GitHub
- URL: https://github.com/graph4ai/graph4nlp_literature
- Owner: graph4ai
- License: mit
- Created: 2020-12-18T04:18:58.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2021-06-06T02:33:19.000Z (over 3 years ago)
- Last Synced: 2024-08-03T23:25:10.696Z (3 months ago)
- Language: Python
- Size: 416 KB
- Stars: 240
- Watchers: 13
- Forks: 32
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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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/)