Few-shot Relation Extraction via Bayesian Meta-learning on Task Graphs. ICML 2020. Qu et al. [Paper]
NERO: A Neural Rule Grounding Framework for Label-Efficient Relation Extraction WWW 2020. Zhou et al.. [Paper]
LOREM: Language-consistent Open Relation Extraction from Unstructured Text. WWW 2020. Harting et al. [Paper]
Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks. NAACL 2019. Ningyu Zhang, Shumin Deng, Zhanlin Sun, Guanying Wang, Xi Chen, Wei Zhang, Huajun Chen. [Paper]
Discovering Correlations between Sparse Features in Distant Supervision for Relation Extraction. WSDM 2019. Qu, Jianfeng and Ouyang, Dantong and Hua, Wen and Ye, Yuxin and Zhou, Xiaofang. [Paper]
A Hierarchical Framework for Relation Extraction with Reinforcement Learning. AAAI 2019. Takanobu, Ryuichi and Zhang, Tianyang and Liu, Jiexi and Huang, Minlie. [Paper] [Code]
Neural Relation Extraction via Inner-Sentence Noise Reduction and Transfer Learning. EMNLP 2018. Liu, Tianyi, Xinsong Zhang, Wanhao Zhou, and Weijia Jia. [Paper] [Note]
DSGAN: Generative Adversarial Training for Robust Distant Supervision Relation Extraction. ACL 2018. Pengda Qin, Weiran Xu, William Yang Wang. [Paper]
Deep Residual Learning for Weakly-Supervised Relation Extraction. EMNLP 2017. Yi Yao Huang, William Yang Wang. [Paper] [Code]
Incorporating Relation Paths in Neural Relation Extraction. EMNLP 2017. Zeng, Wenyuan and Lin, Yankai and Liu, Zhiyuan and Sun, Maosong. [Paper] [Code]
Knowledge-based weak supervision for information extraction of overlapping relations. ACL 2011. Hoffmann, Raphael and Zhang, Congle and Ling, Xiao and Zettlemoyer, Luke and Weld, Daniel S. [Paper]
Learning syntactic patterns for automatic hypernym discovery. NIPS 2005. Snow, Rion and Jurafsky, Daniel and Ng, Andrew Y. [Paper]
Distant supervision for relation extraction without labeled data. ACL 2009. Mintz, Mike and Bills, Steven and Snow, Rion and Jurafsky, Dan. [Paper]
Modeling relations and their mentions without labeled text. ECML 2010. Riedel, Sebastian and Yao, Limin and McCallum, Andrew. [Paper]
Multi-instance multi-label learning for relation extraction. EMNLP 2012. Surdeanu, Mihai and Tibshirani, Julie and Nallapati, Ramesh and Manning, Christopher D. [Paper]
Connecting Language and Knowledge Bases with Embedding Models for Relation Extraction. EMNLP 2013. Weston, Jason and Bordes, Antoine and Yakhnenko, Oksana and Usunier, Nicolas. [Paper]
Distant supervision for relation extraction with matrix completion. ACL 2014. Fan, Miao and Zhao, Deli and Zhou, Qiang and Liu, Zhiyuan and Zheng, Thomas Fang and Chang, Edward Y. [Paper]
Semantic compositionality through recursive matrix-vector spaces. EMNLP 2012. Socher, Richard and Huval, Brody and Manning, Christopher D and Ng, Andrew Y. [Paper]
End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures. ACL 2016. Miwa, Makoto and Bansal, Mohit. [Paper]
Relation Classification via Convolutional Deep Neural Network. COLING 2014. Zeng, Daojian and Liu, Kang and Lai, Siwei and Zhou, Guangyou and Zhao, Jun. [Paper]
Classifying relations via long short term memory networks along shortest dependency paths. EMNLP 2015. Xu, Yan and Mou, Lili and Li, Ge and Chen, Yunchuan and Peng, Hao and Jin, Zhi. [Paper]
Classifying Relations by Ranking with Convolutional Neural Networks. ACL 2015. dos Santos, Cicero and Xiang, Bing and Zhou, Bowen. [Paper]
Distant supervision for relation extraction via piecewise convolutional neural networks. EMNLP 2015. Zeng, Daojian and Liu, Kang and Chen, Yubo and Zhao, Jun. [Paper]
Neural relation extraction with selective attention over instances. ACL 2016. Lin, Yankai and Shen, Shiqi and Liu, Zhiyuan and Luan, Huanbo and Sun, Maosong. [Paper] [Code]
Adversarial training for relation extraction. EMNLP 2017. Wu, Yi and Bamman, David and Russell, Stuart. [Paper] [Code]
Relation Extraction with Multi-instance Multi-label Convolutional Neural Networks. COLING 2016. Jiang, Xiaotian and Wang, Quan and Li, Peng and Wang, Bin. [Paper]
Jointly Extracting Relations with Class Ties via Effective Deep Ranking. ACL 2017. Ye, Hai and Chao, Wenhan and Luo, Zhunchen and Li, Zhoujun [Paper]
A soft-label method for noise-tolerant distantly supervised relation extraction. EMNLP 2017. Liu, Tianyu and Wang, Kexiang and Chang, Baobao and Sui, Zhifang. [Paper]
Distant supervision for relation extraction with sentence-level attention and entity descriptions. AAAI 2017. Ji, Guoliang and Liu, Kang and He, Shizhu and Zhao, Jun. [Paper]
Attention-based convolutional neural network for semantic relation extraction. COLING 2016. Shen, Yatian and Huang, Xuanjing. [Paper]
Neural knowledge acquisition via mutual attention between knowledge graph and text. AAAI 2018. Han, Xu and Liu, Zhiyuan and Sun, Maosong. [Paper] [Code] Also for KGC.
Cooperative Denoising for Distantly Supervised Relation Extraction. COLING 2018. Lei, Kai and Chen, Daoyuan and Li, Yaliang and Du, Nan and Yang, Min and Fan, Wei and Shen, Ying. [Paper]
Hierarchical Relation Extraction with Coarse-to-Fine Grained Attention. EMNLP 2018. Han, Xu and Yu, Pengfei and Liu, Zhiyuan and Sun, Maosong and Li, Peng. [Paper] [Code]
Large scaled relation extraction with reinforcement learning. AAAI 2018. Zeng, Xiangrong and He, Shizhu and Liu, Kang and Zhao, Jun. [Paper]
Robust Distant Supervision Relation Extraction via Deep Reinforcement Learning. ACL 2018. Qin, Pengda and Weiran, XU and Wang, William Yang. [Paper]
Incorporating vector space similarity in random walk inference over knowledge bases. EMNLP 2014. Gardner, Matt and Talukdar, Partha and Krishnamurthy, Jayant and Mitchell, Tom. [Paper]
Bidirectional recurrent convolutional neural network for relation classification. ACL 2016. Cai, Rui and Zhang, Xiaodong and Wang, Houfeng. [Paper]
Attention-based bidirectional long short-term memory networks for relation classification. ACL 2016. Zhou, Peng and Shi, Wei and Tian, Jun and Qi, Zhenyu and Li, Bingchen and Hao, Hongwei and Xu, Bo. [Paper]
Reinforcement learning for relation classification from noisy data. AAAI 2018. Feng, Jun and Huang, Minlie and Zhao, Li and Yang, Yang and Zhu, Xiaoyan. [Paper]