Paper Reading List

Conference Website

Conference DeadLine	2020	2019	2018
ACL	ACL 2020	ACL 2019	ACL 2018
EMNLP	EMNLP 2020	EMNLP 2019	EMNLP 2018
NAACL	-	NAACL 2019	NAACL 2018
COLING	COLING 2020	-	COLING 2018
AAAI	AAAI 2020	AAAI 2019	AAAI 2018
IJCAI	IJCAI 2020	IJCAI 2019	IJCAI 2018

Keyphrase Generation

• Select, Extract and Generate: Neural Keyphrase Generation with Syntactic Guidance. Wasi Uddin Ahmad, Xiao Bai, Soomin Lee, Kai-Wei Chang. arXiv 2020. [paper]
• A Preliminary Exploration of GANs for Keyphrase Generation. Avinash Swaminathan, Haimin Zhang, Debanjan Mahata, Rakesh Gosangi, Rajiv Ratn Shah, Amanda Stent. EMNLP 2020 (short paper). [paper][code]
• One Size Does Not Fit All: Generating and Evaluating Variable Number of Keyphrases. Xingdi Yuan, Tong Wang, Rui Meng, Khushboo Thaker, Peter Brusilovsky, Daqing He, Adam Trischler. ACL 2020. [paper]
• Keyphrase Generation for Scientific Document Retrieval. Florian Boudin, Ygor Gallina, Akiko Aizawa. ACL 2020 (short paper). [paper][code]
• Exclusive Hierarchical Decoding for Deep Keyphrase Generation. Wang Chen, Hou Pong Chan, Piji Li, Irwin King. ACL 2020. [paper][code]
• Keyphrase Generation for Scientific Articles Using GANs. Avinash Swaminathan, Raj Kuwar Gupta, Haimin Zhang, Debanjan Mahata, Rakesh Gosangi, Rajiv Ratn Shah. AAAI 2020 (short paper). [paper][code]
• TAN-NTM: Topic Attention Networks for Neural Topic Modeling. Madhur Panwar, Shashank Shailabh, Milan Aggarwal, Balaji Krishnamurthy. arXiv 2020 [paper]
• Diverse Keyphrase Generation with Neural Unlikelihood Training. Hareesh Bahuleyan, Layla El Asri. COLING 2020. [paper]
• An Empirical Study on Neural Keyphrase Generation. Rui Meng, Xingdi Yuan, Tong Wang, Sanqiang Zhao, Adam Trischler, Daqing He. arXiv 2020. [paper]
• An Integrated Approach for Keyphrase Generation via Exploring the Power of Retrieval and Extraction. Wang Chen, Hou Pong Chan, Piji Li, Lidong Bing, Irwin King. NAACL 2019. [paper][code]
• Incorporating Linguistic Constraints into Keyphrase Generation. Jing Zhao, Yuxiang Zhang. ACL 2019. [paper][code]
• Topic-Aware Neural Keyphrase Generation for Social Media Language. Yue Wang, Jing Li, Hou Pong Chan, Irwin King, Michael R. Lyu, Shuming Shi. ACL 2019. [paper][code]
• Neural Keyphrase Generation via Reinforcement Learning with Adaptive Rewards. Hou Pong Chan, Wang Chen, Lu Wang, Irwin King. ACL 2019. [paper][code]
• Title-Guided Encoding for Keyphrase Generation. Wang Chen, Yifan Gao, Jiani Zhang, Irwin King,Michael R. Lyu. AAAI 2019. [paper]
• Keyphrase Generation: A Text Summarization Struggle. Erion Çano, Ondřej Bojar. NAACL 2019. [paper]
• Keyphrase Generation Using Sequence-to-Sequence Models. Ehsan Doostmohammadi, Mohammad Hadi Bokaei, Hossein Sameti. ICEE 2019. [paper]
• Keyphrase Generation: A Multi-Aspect Survey. Erion Çano, Ondřej Bojar. arXiv 2019. [paper]
• BSDAR: Beam Search Decoding with Attention Reward in Neural Keyphrase Generation. Iftitahu Ni'mah, Vlado Menkovski, Mykola Pechenizkiy. arXiv 2019. [paper]
• Semi-Supervised Learning for Neural Keyphrase Generation. Hai Ye and Lu Wang. EMNLP 2018. [paper]
• Keyphrase Generation with Correlation Constraints. Jun Chen, Xiaoming Zhang, Yu Wu,Zhao Yan,Zhoujun Li. EMNLP 2018. [paper]
• Does Order Matter? An Empirical Study on Generating Multiple Keyphrases as a Sequence. Meng, Rui and Yuan, Xingdi and Wang, Tong and Brusilovsky, Peter and Trischler, Adam and He, Daqing. arXiv 2018. [paper][code]
• Deep Keyphrase Generation. Rui Meng, Sanqiang Zhao, Shuguang Han, Daqing He, Peter Brusilovsky, Yu Chi. ACL 2017. [paper][code]

KeyPhrase Extraction/Prediction

• Cross-Media Keyphrase Prediction: A Unified Framework with Multi-Modality Multi-Head Attention and Image Wordings. Yue Wang, Jing Li, Michael R. Lyu, Irwin King. EMNLP 2020. [paper][code]
• A Review of Keyphrase Extraction. Eirini Papagiannopoulou, Grigorios Tsoumakas. Arxiv 2020. [paper]
• DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases. Zhiqing Sun, Jian Tang, Pan Du, Zhi-Hong Deng, Jian-Yun Nie. SIGIR 2019. [paper]
• Bi-LSTM-CRF Sequence Labeling for Keyphrase Extraction from Scholarly Documents. Rabah A. Al-Zaidy, Cornelia Caragea, C. Lee Giles. WWW 2019. [paper]
• Simple Unsupervised Keyphrase Extraction using Sentence Embeddings. Kamil Bennani-Smires, Claudiu Musat, Andreea Hossmann, Michael Baeriswyl, Martin Jaggi. CONLL 2018. [paper]
• Bidirectional LSTM recurrent neural network for keyphrase extraction. Basaldella, M., Antolli, E., Serra, G. and Tasso, C. IRCDL 2018. [paper]
• Simple unsupervised keyphrase extraction using sentence embeddings. Bennani-Smires, K., Musat, C., Hossmann, A., Baeriswyl, M. and Jaggi, M. CONLL 2018. [paper]
• Unsupervised keyphrase extraction with multipartite graphs. Boudin, F. NAACL 2018. [paper]
• PositionRank: An unsupervised approach to keyphrase extraction from scholarly documents. Florescu, C. and Caragea, C. ACL 2017. [paper]
• Incorporating expert knowledge into keyphrase extraction. Gollapalli, S. D., Li, X. and Yang, P. AAAI 2017. [paper]
• Keyphrase annotation with graph co-ranking. Bougouin, A., Boudin, F. and Daille, B. COLING 2016. [paper]
• TopicRank: Graph-based topic ranking for keyphrase extraction. Adrien Bougouin and Florian Boudin and Beatrice Daille. IJCNLP 2013. [paper]
• Extracting keyphrases from research papers using citation networks. Bougouin, A., Boudin, F. and Daille, B. IJCNLP 2013. [paper]

Distantly Relation Extraction

• Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction. Yang Li, Guodong Long, Tao Shen, Tianyi Zhou, Lina Yao, Huan Huo, Jing Jiang. AAAI 2020. [paper]
• Are Noisy Sentences Useless for Distant Supervised Relation Extraction?. Yu-Ming Shang, He-Yan Huang, Xian-Ling Mao, Xin Sun,Wei Wei. AAAI 2020. [paper]
• Improving Neural Relation Extraction with Positive and Unlabeled Learning. Zhengqiu He and Wenliang Chen and Yuyi Wang, Wei Zhang and Guanchun Wang and Min Zhang. AAAI 2020. [paper]
• Fine-tuning pre-Train Transformer Language Models to Distantly Supervised Relation Etraction. Christoph Alt, Marc Hübner, Leonhard Hennig. ACL 2019. [paper] [code]
• DIAG-NRE: A Neural pattern Diagnosis Framwork for Distantly Supervised Neural Relation Extraction. ACL 2019. Shun Zheng, Xu Han, Yankai Lin, Peilin Yu, Lu Chen, Ling Huang, Zhiyuan Liu, Wei Xu [paper]
• **ARNOR: Attention Regularization based Noise Reduction for Distant Supervision Relation Classification. ** Wei Jia, Dai Dai, Xinyan Xiao and Hua Wu. ACL 2019. [paper]
• Uncover the Ground-Truth Relations in Distant Supervision: A Neural Expectation Maximization Framework. Junfan Chen, Richong Zhang, Yongyi Mao, Hongyu Guo and Jie Xu. EMNLP 2019. [paper]
• Self-Attention Enhanced CNNs and Collaborative Curriculum Learning for Distantly Supervised Relation Extraction. Yuyun Huang and Jinhua Du. EMNLP 2019. [paper]
• Looking Beyond Label Noise: Shifted Label Distribution Matters in Distantly Supervised Relation Extraction. Linmei Hu, Luhao Zhang, Chuan Shi, Liqiang Nie, Weili Guan and Cheng Yang. EMNLP 2019. [paper]
• Improving Distantly-Supervised Relation Extraction with Joint Label Embedding. Qinyuan Ye, Liyuan Liu, Maosen Zhang and Xiang Ren. EMNLP 2019. [paper]
• Leveraging 2-hop Distant Supervision from Table Entity Pairs for Relation Extraction. Xiang Deng and Huan Sun. EMNLP 2019.[paper]
• Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolutino Networks. Ningyu Zhang, Shumin Deng, Zhanlin Sun, Guanying Wang, Xi Chen, Wei Zhang, Huajun Chen. NAACL 2019. [paper]
• Distant Supervision Relation Extraction with Intra-Bag and Inter-Bag Attentions. Zhi-Xiu Ye, Zhen-Hua Ling. NAACL 2019. [paper]
• Exploiting Noisy Data in Distant Supervison Relation Classification. Kaijia Yang, Liang He, Xin-yu Dai, Shujian Huang, Jiajun Chen. NAACL 2019. [paper]
• GAN driven Semi-distant Supervison for Relation Extraction. Pengshuai Li, Xinsong Zhang, Weijia Jia, Hai Zhao. NAACL 2019. [paper]
• Cross-relation Cross-bag Attention for Distantly-supervised Relation Extraction. Yujin Yuan, Liyuan Liu, Siliang Tang , Zhongfei Zhang, Yueting Zhuang, Shiliang Pu, Fei Wu, Xiang Ren. AAAI 2019. [paper]
• Relation Extraction Using Supervision from Topic Knowledge of Relation Labels. Haiyun Jiang, Li Cui, Zhe Xu, Deqing Yang, Jindong Chen, Chenguang Li, Jingping Liu, Jiaqing Liang, Chao Wang, Yanghua Xiao, Wei Wang IJCAI 2019. [paper]
• Robust Distant Supervision Relation Extraction via Deep Reinforcement Learning. Pengda Qin, Weiran Xu, William Yang Wang ACL 2018. [paper]
• DSGAN: Generative Adversarial Training for Distant Supervision Relation Extraction. Pengda Qin, Weiran Xu, William Yang Wang. ACL 2018. [paper]
• Attention-Based Capsule Networks with Dynamic Routing for Relation Extraction. Ningyu Zhang, Shumin Deng, Zhanlin Sun, Xi Chen, Wei Zhang, Huajun Chen ACL 2018. [short paper]
• Label-Free Distant Supervision for Relation Extraction via Knowledge Graph Embedding. Guanying Wang, Wen Zhang, Ruoxu Wang, Yalin Zhou, Xi Chen, Wei Zhang, Hai Zhu, Huajun Chen. EMNLP 2018. [paper]
• RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information. Shikhar Vashishth, Rishabh Joshi, Sai Suman Prayaga, Chiranjib Bhattacharyya, Partha Talukdar. EMNLP 2018. [paper]
• Hierarchical Relation Extraction with Coarse-to-Fine Grained Attention. Xu Han, Pengfei Yu, Zhiyuan Liu, Maosong Sun, Peng Li. EMNLP 2018. [paper]
• Multi-Level Structured Self-Attentions for Distantly Supervised Relation Extraction. Jinhua Du, Jingguang Han, Andy Way, Dadong Wan. EMNLP 2018. [paper]
• Cooperative Denoising for Distantly Supervised Relation Extraction. Kai Lei, Daoyuan Chen, Yaliang Li, Nan Du, Min Yang, Wei Fan, Ying Shen. COLING 2018. [paper]
• Large Scaled Relation Extraction with Reinforcement Learning. AAAI 2018. [[paper]
• Reinforcement Learning for Relation Classification from Noisy Data. AAAI 2018. [paper]
• Exploring Encoder-Decoder Model for Distant Supervised Relation Extraction. IJCAI 2018. [paper]
• Neural Relation Extraction with Selective Attention over Instances. Yankai Lin, Shiqi Shen, Zhiyuan Liu,, Huanbo Luan, Maosong Sun. ACL 2016. [paper]
• Relation Extraction with Multi-instance Multi-label Convolutional Neural Networks. COLING 2016. [paper]
• Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks. Daojian Zeng, Kang Liu, Yubo Chen and Jun Zhao. EMNLP 2015. [paper]
• Multi-Task Transfer Learning for Weakly-Supervised Relation Extraction. Jing Jiang. ACL2010. [paper]

Few-shot Relation Rxtraction

• Fewrel: A large-scale supervised few-shot relation classification dataset with state-of-the-art evaluation. Xu Han, Hao Zhu, Pengfei Yu, ZiyunWang, Yuan Yao, Zhiyuan Liu, and Maosong Sun. EMNLP 2018. [paper]
• FewRel 2.0: Towards more challenging few-shot relation classification. Tianyu Gao, Xu Han, Hao Zhu, Zhiyuan Liu, Peng Li, Maosong Sun, and Jie Zhou. EMNLP2019. [paper]
• Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification. Tianyu Gao, Xu Han, Zhiyuan Liu, Maosong Sun. AAAI 2019. [paper]
• Matching the blanks: Distributional similarity for relation learning. Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling, and Tom Kwiatkowski. ACL 2019. [paper]
• Multi-level matching and aggregation network for few-shot relation classification. Zhi-Xiu Ye and Zhen-Hua Ling. ACL 2019. [paper]

Document-level Relation Rxtraction

• Double Graph Based Reasoning for Document-level Relation Extraction. Shuang Zeng, Runxin Xu, Baobao Chang and Lei Li. EMNLP2020. [paper]
• Global-to-Local Neural Networks for Document-Level Relation Extraction. Difeng Wang, Wei Hu, Ermei Cao and Weijian Sun. EMNLP2020. [paper]
• Denoising Relation Extraction from Document-level Distant Supervision. Chaojun Xiao, Yuan Yao, Ruobing Xie, Xu Han, Zhiyuan Liu, Maosong Sun, Fen Lin and Leyu Lin. EMNLP2020. [short paper]

Other Relation Rxtraction (Supervied, OpenIE, Overview, etc.)

• Joint Constrained Learning for Event-Event Relation Extraction. Haoyu Wang, Muhao Chen, Hongming Zhang and Dan Roth. EMNLP2020. [paper]
• Learning from Context or Names? An Empirical Study on Neural Relation Extraction. Hao Peng, Tianyu Gao, Xu Han, Yankai Lin, Peng Li, Zhiyuan Liu, Maosong Sun and Jie Zhou. EMNLP2020. [paper]
• SelfORE: Self-supervised Relational Feature Learning for Open Relation Extraction. Xuming Hu, Lijie Wen, Yusong Xu, Chenwei Zhang and Philip Yu. EMNLP2020. [paper]
• TED-CDB: A Large-Scale Chinese Discourse Relation Dataset on TED Talks. Wanqiu Long, Bonnie Webber, Deyi Xiong [paper]
• Domain Knowledge Empowered Structured Neural Net for End-to-End Event Temporal Relation Extraction Rujun Han, Yichao Zhou and Nanyun Peng. EMNLP2020. [paper]
• Within-Between Lexical Relation Classification. Oren Barkan, Avi Caciularu and Ido Dagan. EMNLP2020. [short paper]
• More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction. Xu Han, Tianyu Gao, Yankai Lin, Hao Peng, Yaoliang Yang, Chaojun Xiao, Zhiyuan Liu. arxiv. [paper]
• Integrating Relation Constraints with Neural Relation Extractors. ZYuan Ye, Yansong Feng, Bingfeng Luo, Yuxuan Lai, Dongyan Zhao. AAAI 2020. [paper]
• Distilling Knowledge from Well-informed Soft Labels. Zhenyu Zhang, Xiaobo Shu, Bowen Yu, Tingwen Liu, Jiapeng Zhao, Quangang Li, Li Guo. AAAI 2020. [paper]
• Relation Extraction Exploiting Full Dependency Forests. Lifeng Jin, Linfeng Song, Yue Zhang, Kun Xu, Wei-yun Ma and Dong Yu. AAAI 2020. [paper]
• NERO: A Neural Rule Grounding Framework for Label-Efficient Relation Extraction. Wenxuan Zhou, Hongtao Lin, Bill Yuchen Lin, Ziqi Wang, Junyi Du, Leonardo Neves, Xiang Ren. WWW 2020. [paper]
• Exploiting Entity BIO Tag Embeddings and Multi-task Learning for Relation Extraction with Imbalanced Data. Wei Ye, Bo Li, Rui Xie, Zhonghao Sheng, Long Chen, Shikun Zhang. ACL 2019. [paper]
• Fine-Grained Temporal Relation Extraction . Siddharth Vashishtha -University of Rochester . [paper]

Multi-label classification

• Multi-Label Learning with Global and Local Label Correlation
• Exploring Correlation between Labels to improve Multi-Label Classification
• Multi-Label Learning by Exploiting Label Correlations Locally
• SGM: Sequence Generation Model for Multi-label Classification
• Deep Learning with a Rethinking Structure for Multi-label Classification

Hierarchical Classification

• Hierarchical Text Classification with Reinforced Label Assignment. EMNLP2019. [paper]
• A survey of hierarchical classification across different application domains. 2012.[paper]
• Top-down Strategies for Hierarchical Classification of Transposable Elements with Neural Networks. Felipe Kenji Nakano. ICACCT 2017.[paper]
• 大规模分类任务的分层学习 胡清华 [paper]

Label Embedding, Label-Specific

• Label Embedding for Zero-shot Fine-grained Named Entity Typing Yukun Ma, Erik Cambria, Sa Gao. COLING 2016. [paper]
• Description-Based Zero-shot Fine-Grained Entity Typing Rasha Obeidat, Xiaoli Fern, Hamed Shahbazi and Prasad Tadepalli. NAACL 2019. [paper]
• Employing the Correspondence of Relations and Connectives to Identify Implicit Discourse Relations via Label Embeddings Linh The Nguyen,Linh Van Ngo†,Khoat Than† and Thien Huu Nguyen. ACL 2019. [short paper]
• Label-Specific Document Representation for Multi-Label Text Classification Xiao, Lin and Huang, Xin and Chen, Boli and Jing, Liping. EMNLPL 2019.[paper] [code]
• Hierarchically-Refined Label Attention Network for Sequence Labeling Leyang Cui and Yue Zhang. EMNLPL 2019. [paper]
• Rethinking Self-Attention: Towards Interpretability in Neural Parsing Khalil Mrini, Franck Dernoncourt, Trung Bui, Walter Chang, Ndapa Nakashole. [paper]
• Multi-Task Label Embedding for Text Classification. Honglun Zhang, Liqiang Xiao, Wenqing Chen, Yongkun Wang, Yaohui Jin [paper]

Avaiable Tecnology

• Hierarchical Entity Typing via Multi-level Learning to Rank. ACL2020. [paper]
• A Deep Reinforced Sequence-to-Set Model for Multi-Label Text Classification. AAAI2019. [paper]
• Representation Learning of Knowledge Graphs with Hierarchical Types. IJCAI 2016.[paper]
• Multi-Label Zero-Shot Learning with Structured Knowledge Graphs. CVPR. [paper]
• PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long Text Generation. Xinyu Hua, Lu Wang. EMNLP 2020. [paper]
• Learning to Create Better Ads: Generation and Ranking Approaches for Ad Creative Refinement. Shaunak Mishra, Manisha Verma, Yichao Zhou, Kapil Thadani, Wei Wang. CIKM 2020. [paper]
• Diverse, Controllable, and Keyphrase-Aware: A Corpus and Method for News Multi-Headline Generation. Dayiheng Liu, Yeyun Gong, Jie Fu, Wei Liu, Yu Yan, Bo Shao, Daxin Jiang, Jiancheng Lv, Nan Duan. EMNLP 2020. [paper]
• Sentence-Level Content Planning and Style Specification for Neural Text Generation. Xinyu Hua, Lu Wang. EMNLP 2019. [paper]
• WriterForcing: Generating more interesting story endings. Xinyu Hua, Lu Wang. ACL Workshop 2019. [paper]

Resources

• FunNLP
• OpenNRE