└── README.md /README.md: -------------------------------------------------------------------------------- 1 | ## Must-read papers on RE. 2 | RE: relation extraction. 3 | 4 | Contributed by [Ningyu Zhang](https://zxlzr.github.io/). 5 | 6 | [OpenNRE](https://github.com/thunlp/OpenNRE) an open source toolkit for NRE. 7 | 8 | ### DS Methods 9 | 10 | 11 | 1. Large Scaled Relation Extraction with Reinforcement Learning (AAAI-18) 12 | 13 | 1. Reinforcement Learning for Relation Extraction from Noisy Data (AAAI-18) 14 | 15 | 1. Distant Supervision for Relation Extraction with Sentence-Level Attention and Entity Descriptions (AAAI-17) 16 | 17 | 1. SEE: Syntax-aware Entity Embedding for Neural Relation Extraction (AAAI-18) 18 | 19 | 1. DSGAN: Generative Adversarial Training for Distant Supervision Relation Extraction (ACL-18) 20 | 21 | 1. Neural Knowledge Acquisition via Mutual Attention between Knowledge Graph and Text (AAAI-18) 22 | 23 | 1. Adversarial Multi-lingual Neural Relation Extraction (Coling-18) 24 | 25 | 1. Ensemble Neural Relation Extraction with Adaptive Boosting (IJCAI-18) 26 | 27 | 1. Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme (IJCAI-18) 28 | 29 | 1. Exploring Encoder-Decoder Model for Distant Supervised Relation Extraction (IJCAI-18) 30 | 31 | 1. Global Relation Embedding for Relation Extraction (NAACL) 32 | 33 | 1. Denoising Distant Supervision for Relation Extraction via Instance-Level Adversarial Training (Arxiv-18) 34 | 35 | 1. Jointly Extracting Relations with Class Ties via Effective Deep Ranking (ACL-17) 36 | 37 | 1. Neural Relation Extraction with Multi-lingual Attention (ACL-17) 38 | 39 | 1. Incorporating Relation Paths in Neural Relation Extraction (EMNLP-17) 40 | 41 | 1. Context-Aware Representations for Knowledge Base Relation Extraction (EMNLP-17) 42 | 43 | 1. Adversarial Training for Relation Extraction (EMNLP-17) 44 | 45 | 1. Effective Deep Memory Networks for Distant Supervised Relation Extraction (IJCAI-17) 46 | 47 | 1. ENCORE : External Neural Constraints Regularized Distant Supervision for Relation Extraction (Sigir-17) 48 | 49 | 1. Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks (EMNLP-15) 50 | 51 | 1. Deep Residual Learning for Weakly-Supervised Relation Extraction (EMNLP-17) 52 | 53 | 1. Neural Relation Extraction with Selective Attention over Instances (ACL-16) 54 | 55 | 1. Relation Extraction with Multi-instance Multi-label Convolutional Neural Networks (Coling-16) 56 | 57 | 1. Distant Supervision for Relation Extraction beyond the Sentence Boundary (ECAL-16) 58 | 59 | 1. Noise-Clustered Distant Supervision for Relation Extraction: A Nonparametric Bayesian Perspective (EMNLP-17) 60 | 61 | 1. Distant Supervision for Relation Extraction with Matrix Completion (ACL-14) 62 | 63 | 1. Learning with Noise: Enhance Distantly Supervised Relation Extraction with Dynamic Transition Matrix (ACL-17) 64 | 65 | 1. Indirect Supervision for Relation Extraction using Question-Answer Pairs (WSDM-18) 66 | 67 | 1. CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases (WWW-17) 68 | 69 | 1. Weakly-supervised Relation Extraction by Pattern-enhanced Embedding Learning (WWW-18) 70 | 71 | 1. Heterogeneous Supervision for Relation Extraction: A Representation Learning Approach (EMNLP-17) 72 | 73 | 1. Cooperative Denoising for Distantly Supervised Relation Extraction (Coling-18) 74 | 75 | 1. Attention-Based Capsule Networks with Dynamic Routing for Relation Extractionn (EMNLP-18) 76 | 77 | 1. Label-Free Distant Supervision for Relation Extraction via Knowledge Graph Embedding (EMNLP-18) 78 | 79 | ### Supervised 80 | 81 | 1. Relation Classification via Multi-Level Attention CNNs (ACL-16) 82 | 83 | 1. Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification (ACL-16) 84 | 85 | 1. A Walk-based Model on Entity Graphs for Relation Extraction (ACL-18) 86 | 87 | 1. End-to-End Neural Relation Extraction with Global Optimization (EMNLP-17) 88 | 89 | 1. Cross-Sentence N-ary Relation Extraction with Graph LSTMs (ACL-17) 90 | 91 | 1. End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures (ACL-16) 92 | 93 | 1. Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification (ACL-16) 94 | 95 | 1. Relation Extraction with Matrix Factorization and Universal Schemas (NAACL-13) 96 | 97 | 1. Classifying Relations by Ranking with Convolutional Neural Networks (ACL-15) 98 | 99 | ## Domain Adaption 100 | 101 | 1. Generalizing Biomedical Relation Classification with Neural Adversarial Domain Adaptation (Bioinformatics-18) 102 | 103 | 1. Domain Adaptation for Relation Extraction with Domain Adversarial Neural Network (IJCNLP-17) 104 | 105 | 1. Semantic Representations for Domain Adaptation : A Case Study on the Tree Kernel-based Method for Relation Extraction (ACL-15) 106 | 107 | 1. Robust Domain Adaptation for Relation Extraction via Clustering Consistency (ACL-14) 108 | 109 | 1. Employing Word Representations and Regularization for Domain Adaptation of Relation Extraction (ACL-14) 110 | 111 | 1. Embedding Semantic Similarity in Tree Kernels for Domain Adaptation of Relation Extraction (ACL-13) 112 | 113 | 1. Relation Adaptation: Domain Adaptation of Relation Extraction Systems (ACL-11) (Adapt to new relation) 114 | 115 | 1. Multi-Task Transfer Learning for Weakly-Supervised Relation Extraction (ACL-09) (Adapt to new relation) 116 | 117 | 1. Relation Adaptation : Learning to Extract Novel Relations with Minimum Supervision (IJCAI-11) (Adapt to new relation) 118 | 119 | # Others 120 | 121 | 1. Relation Adaptation : Learning to Extract Novel Relations with Minimum Supervision (IJCAI-11) 122 | 123 | 1. Zero-Shot Relation Extraction via Reading Comprehension (CoNLL-17) 124 | 125 | --------------------------------------------------------------------------------