createrll/awesome_information_extraction

Literature Survey of Information Extraction, especially Relation Extraction, Event Extraction, and Slot Filling.

Information Extraction Literature

This repository is maintained by Tongtong Wu. Please don't hesitate to send me an email to collaborate or fix some entries (wutong8023 AT gmail.com). The automation script of this repo is powered by Auto-Bibfile.

You can directly use our bibtex.bib in overleaf with this link.

This page categorizes the literature by the Published Venue.

Outline

• 
• 
• 
• 
• 
• 
• 
• 
• 
• 
• 
• 
• 
• 
• 
• 
• 
• 
• 
• 
• 

Hyperlink

• [Overview] -- Homepage
• [NLP] [CV] -- Summary
• [NLP] [CV] -- Application
• [NLP] [CV] -- Approach
• [NLP] [CV] -- Author
• [NLP] [CV] -- Backbone Model
• [NLP] [CV] -- Contribution
• [NLP] [CV] -- Dataset
• [NLP] [CV] -- Metrics
• [NLP] [CV] -- Research Questions
• [NLP] [CV] -- Setting
• [NLP] [CV] -- Learning Paradigm
• [NLP] [CV] -- Published Time
• [NLP] [CV] -- Published Venue

ACL

• Adaptive Knowledge-Enhanced Bayesian Meta-Learning for Few-shot Event Detection ,
  by Shirong Shen and Tongtong Wu and Guilin Qi and Yuan{-}Fang Li and Gholamreza Haffari and Sheng Bi [bib]
  

  ShenWQLHB21

• Document-level Event Extraction via Parallel Prediction Networks ,
  by Yang, Hang and Sui, Dianbo and Chen, Yubo and Liu, Kang and Zhao, Jun and Wang, Taifeng [bib]
  

  yang-etal-2021-document

• CLEVE: Contrastive Pre-training for Event Extraction ,
  by Wang, Ziqi and Wang, Xiaozhi and Han, Xu and Lin, Yankai and Hou, Lei and Liu, Zhiyuan and Li, Peng and Li, Juanzi and Zhou, Jie [bib]
  

  wang-etal-2021-cleve

• PRGC: Potential Relation and Global Correspondence Based Joint Relational Triple Extraction ,
  by Zheng, Hengyi and Wen, Rui and Chen, Xi and Yang, Yifan and Zhang, Yunyan and Zhang, Ziheng and Zhang, Ningyu and Qin, Bin and Ming, Xu and Zheng, Yefeng [bib]
  

  zheng-etal-2021-prgc

• TIMERS: Document-level Temporal Relation Extraction ,
  by Mathur, Puneet and Jain, Rajiv and Dernoncourt, Franck and Morariu, Vlad and Tran, Quan Hung and Manocha, Dinesh [bib]
  

  mathur-etal-2021-timers

• Few-NERD: A Few-shot Named Entity Recognition Dataset ,
  by Ding, Ning and Xu, Guangwei and Chen, Yulin and Wang, Xiaobin and Han, Xu and Xie, Pengjun and Zheng, Haitao and Liu, Zhiyuan [bib]
  

  ding-etal-2021-nerd

• Argument Pair Extraction via Attention-guided Multi-Layer Multi-Cross Encoding ,
  by Cheng, Liying and Wu, Tianyu and Bing, Lidong and Si, Luo [bib]
  

  cheng-etal-2021-argument

• UniRE: A Unified Label Space for Entity Relation Extraction ,
  by Wang, Yijun and Sun, Changzhi and Wu, Yuanbin and Zhou, Hao and Li, Lei and Yan, Junchi [bib]
  

  wang-etal-2021-unire

• Addressing Semantic Drift in Generative Question Answering with Auxiliary Extraction ,
  by Li, Chenliang and Bi, Bin and Yan, Ming and Wang, Wei and Huang, Songfang [bib]
  

  li-etal-2021-addressing

• Refining Sample Embeddings with Relation Prototypes to Enhance Continual Relation Extraction ,
  by Cui, Li and Yang, Deqing and Yu, Jiaxin and Hu, Chengwei and Cheng, Jiayang and Yi, Jingjie and Xiao, Yanghua [bib]
  

  cui-etal-2021-refining

• Entity Concept-enhanced Few-shot Relation Extraction ,
  by Yang, Shan and Zhang, Yongfei and Niu, Guanglin and Zhao, Qinghua and Pu, Shiliang [bib]
  

  yang-etal-2021-entity

• Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction ,
  by Lu, Yaojie and Lin, Hongyu and Xu, Jin and Han, Xianpei and Tang, Jialong and Li, Annan and Sun, Le and Liao, Meng and Chen, Shaoyi [bib]
  

  lu-etal-2021-text2event

• Dependency-driven Relation Extraction with Attentive Graph Convolutional Networks ,
  by Tian, Yuanhe and Chen, Guimin and Song, Yan and Wan, Xiang [bib]
  

  tian-etal-2021-dependency

• Knowledgeable or Educated Guess? Revisiting Language Models as Knowledge Bases ,
  by Cao, Boxi and Lin, Hongyu and Han, Xianpei and Sun, Le and Yan, Lingyong and Liao, Meng and Xue, Tong and Xu, Jin [bib]
  

  cao-etal-2021-knowledgeable

• How Knowledge Graph and Attention Help? A Qualitative Analysis into Bag-level Relation Extraction ,
  by Hu, Zikun and Cao, Yixin and Huang, Lifu and Chua, Tat-Seng [bib]
  

  hu-etal-2021-knowledge

• Trigger is Not Sufficient: Exploiting Frame-aware Knowledge for Implicit Event Argument Extraction ,
  by Wei, Kaiwen and Sun, Xian and Zhang, Zequn and Zhang, Jingyuan and Zhi, Guo and Jin, Li [bib]
  

  wei-etal-2021-trigger

• Element Intervention for Open Relation Extraction ,
  by Liu, Fangchao and Yan, Lingyong and Lin, Hongyu and Han, Xianpei and Sun, Le [bib]
  

  liu-etal-2021-element

• CoRI: Collective Relation Integration with Data Augmentation for Open Information Extraction ,
  by Jiang, Zhengbao and Han, Jialong and Sisman, Bunyamin and Dong, Xin Luna [bib]
  

  jiang-etal-2021-cori

• Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker ,
  by Xu, Runxin and Liu, Tianyu and Li, Lei and Chang, Baobao [bib]
  

  xu-etal-2021-document

• Revisiting the Negative Data of Distantly Supervised Relation Extraction ,
  by Xie, Chenhao and Liang, Jiaqing and Liu, Jingping and Huang, Chengsong and Huang, Wenhao and Xiao, Yanghua [bib]
  

  xie-etal-2021-revisiting

• Joint Biomedical Entity and Relation Extraction with Knowledge-Enhanced Collective Inference ,
  by Lai, Tuan and Ji, Heng and Zhai, ChengXiang and Tran, Quan Hung [bib]
  

  lai-etal-2021-joint

• SENT: Sentence-level Distant Relation Extraction via Negative Training ,
  by Ma, Ruotian and Gui, Tao and Li, Linyang and Zhang, Qi and Huang, Xuanjing and Zhou, Yaqian [bib]
  

  ma-etal-2021-sent

• StereoRel: Relational Triple Extraction from a Stereoscopic Perspective ,
  by Tian, Xuetao and Jing, Liping and He, Lu and Liu, Feng [bib]
  

  tian-etal-2021-stereorel

• CIL: Contrastive Instance Learning Framework for Distantly Supervised Relation Extraction ,
  by Chen, Tao and Shi, Haizhou and Tang, Siliang and Chen, Zhigang and Wu, Fei and Zhuang, Yueting [bib]
  

  chen-etal-2021-cil

• From Discourse to Narrative: Knowledge Projection for Event Relation Extraction ,
  by Tang, Jialong and Lin, Hongyu and Liao, Meng and Lu, Yaojie and Han, Xianpei and Sun, Le and Xie, Weijian and Xu, Jin [bib]
  

  tang-etal-2021-discourse

• Zero-shot Event Extraction via Transfer Learning: Challenges and Insights ,
  by Lyu, Qing and Zhang, Hongming and Sulem, Elior and Roth, Dan [bib]
  

  lyu-etal-2021-zero

• ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction ,
  by Lee, Chen-Yu and Li, Chun-Liang and Wang, Chu and Wang, Renshen and Fujii, Yasuhisa and Qin, Siyang and Popat, Ashok and Pfister, Tomas [bib]
  

  lee-etal-2021-rope

• Three Sentences Are All You Need: Local Path Enhanced Document Relation Extraction ,
  by Huang, Quzhe and Zhu, Shengqi and Feng, Yansong and Ye, Yuan and Lai, Yuxuan and Zhao, Dongyan [bib]
  

  huang-etal-2021-three

• A Joint Neural Model for Information Extraction with Global Features ,
  by Lin, Ying and Ji, Heng and Huang, Fei and Wu, Lingfei [bib]
  

  lin-etal-2020-joint

• TXtract: Taxonomy-Aware Knowledge Extraction for Thousands of Product Categories ,
  by Karamanolakis, Giannis and Ma, Jun and Dong, Xin Luna [bib]
  

  karamanolakis-etal-2020-txtract

• ZeroShotCeres: Zero-Shot Relation Extraction from Semi-Structured Webpages ,
  by Lockard, Colin and Shiralkar, Prashant and Dong, Xin Luna and Hajishirzi, Hannaneh [bib]
  

  lockard-etal-2020-zeroshotceres

• Exploiting the Syntax-Model Consistency for Neural Relation Extraction ,
  by Pouran Ben Veyseh, Amir and Dernoncourt, Franck and Dou, Dejing and Nguyen, Thien Huu [bib]
  

  pouran-ben-veyseh-etal-2020-exploiting

• SciREX: A Challenge Dataset for Document-Level Information Extraction ,
  by Jain, Sarthak and van Zuylen, Madeleine and Hajishirzi, Hannaneh and Beltagy, Iz [bib]
  

  jain-etal-2020-scirex

• Revisiting Unsupervised Relation Extraction ,
  by Tran, Thy Thy and Le, Phong and Ananiadou, Sophia [bib]
  

  tran-etal-2020-revisiting

• Relation Extraction with Explanation ,
  by Shahbazi, Hamed and Fern, Xiaoli and Ghaeini, Reza and Tadepalli, Prasad [bib]
  

  shahbazi-etal-2020-relation

• Relabel the Noise: Joint Extraction of Entities and Relations via Cooperative Multiagents ,
  by Chen, Daoyuan and Li, Yaliang and Lei, Kai and Shen, Ying [bib]
  

  chen-etal-2020-relabel

• IMoJIE: Iterative Memory-Based Joint Open Information Extraction ,
  by Kolluru, Keshav and Aggarwal, Samarth and Rathore, Vipul and {Mausam} and Chakrabarti, Soumen [bib]
  

  kolluru-etal-2020-imojie

• Dialogue-Based Relation Extraction ,
  by Yu, Dian and Sun, Kai and Cardie, Claire and Yu, Dong [bib]
  

  yu-etal-2020-dialogue

• Cross-media Structured Common Space for Multimedia Event Extraction ,
  by Li, Manling and Zareian, Alireza and Zeng, Qi and Whitehead, Spencer and Lu, Di and Ji, Heng and Chang, Shih-Fu [bib]
  

  li-etal-2020-cross

• TACRED Revisited: A Thorough Evaluation of the TACRED Relation Extraction Task ,
  by Alt, Christoph and Gabryszak, Aleksandra and Hennig, Leonhard [bib]
  

  alt-etal-2020-tacred

• Probing Linguistic Features of Sentence-Level Representations in Neural Relation Extraction ,
  by Alt, Christoph and Gabryszak, Aleksandra and Hennig, Leonhard [bib]
  

  alt-etal-2020-probing

• Named Entity Recognition without Labelled Data: A Weak Supervision Approach ,
  by Lison, Pierre and Barnes, Jeremy and Hubin, Aliaksandr and Touileb, Samia [bib]
  

  lison-etal-2020-named

• In Layman's Terms: Semi-Open Relation Extraction from Scientific Texts ,
  by Kruiper, Ruben and Vincent, Julian and Chen-Burger, Jessica and Desmulliez, Marc and Konstas, Ioannis [bib]
  

  kruiper-etal-2020-laymans

• A Novel Cascade Binary Tagging Framework for Relational Triple Extraction ,
  by Wei, Zhepei and Su, Jianlin and Wang, Yue and Tian, Yuan and Chang, Yi [bib]
  

  wei-etal-2020-novel

• Document-Level Event Role Filler Extraction using Multi-Granularity Contextualized Encoding ,
  by Xinya Du and Claire Cardie [bib]
  

  DuC20

• Multi-Sentence Argument Linking ,
  by Seth Ebner and Patrick Xia and Ryan Culkin and Kyle Rawlins and Benjamin Van Durme [bib]
  

  EbnerXCRD20

• Reasoning with Latent Structure Refinement for Document-Level Relation Extraction ,
  by Guoshun Nan and Zhijiang Guo and Ivan Sekulic and Wei Lu [bib]
  

  NanGSL20

• A Two-Step Approach for Implicit Event Argument Detection ,
  by Zhisong Zhang and Xiang Kong and Zhengzhong Liu and Xuezhe Ma and Eduard H. Hovy [bib]
  

  ZhangKLMH20

• GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction ,
  by Tsu{-}Jui Fu and Peng{-}Hsuan Li and Wei{-}Yun Ma [bib]
  

  FuLM19

• Graph Neural Networks with Generated Parameters for Relation Extraction ,
  by Hao Zhu and Yankai Lin and Zhiyuan Liu and Jie Fu and Tat{-}Seng Chua and Maosong Sun [bib]
  

  ZhuLLFCS19

• Matching the Blanks: Distributional Similarity for Relation Learning ,
  by Livio Baldini Soares and Nicholas FitzGerald and Jeffrey Ling and Tom Kwiatkowski [bib] MTB
  

  SoaresFLK19

• Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification ,
  by Zhi{-}Xiu Ye and Zhen{-}Hua Ling [bib] MLMAN
  

  YeL19

• DocRED: A Large-Scale Document-Level Relation Extraction Dataset ,
  by Yao, Yuan and Ye, Deming and Li, Peng and Han, Xu and Lin, Yankai and Liu, Zhenghao and Liu, Zhiyuan and Huang, Lixin and Zhou, Jie and Sun, Maosong [bib]
  

  yao-etal-2019-docred

• Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism ,
  by Xiangrong Zeng and Daojian Zeng and Shizhu He and Kang Liu and Jun Zhao [bib]
  

  LiuZZHZ18

• Creating Training Corpora for NLG Micro-Planners ,
  by Claire Gardent and Anastasia Shimorina and Shashi Narayan and Laura Perez{-}Beltrachini [bib]
  

  GardentSNP17

• The Stanford CoreNLP Natural Language Processing Toolkit ,
  by Christopher D. Manning and Mihai Surdeanu and John Bauer and Jenny Rose Finkel and Steven Bethard and David McClosky [bib]
  

  ManningSBFBM14

• Incremental Joint Extraction of Entity Mentions and Relations ,
  by Qi Li and Heng Ji [bib]
  

  LiJ14

• Exploiting Syntactico-Semantic Structures for Relation Extraction ,
  by Yee Seng Chan and Dan Roth [bib]
  

  ChanR11

• Exploring Various Knowledge in Relation Extraction ,
  by Guodong Zhou and Jian Su and Jie Zhang and Min Zhang [bib]
  

  ZhouSZZ05

EMNLP

• MAVEN: A Massive General Domain Event Detection Dataset ,
  by Wang, Xiaozhi and Wang, Ziqi and Han, Xu and Jiang, Wangyi and Han, Rong and Liu, Zhiyuan and Li, Juanzi and Li, Peng and Lin, Yankai and Zhou, Jie [bib]
  

  wang-etal-2020-maven

• Knowledge-guided Open Attribute Value Extraction with Reinforcement Learning ,
  by Liu, Ye and Zhang, Sheng and Song, Rui and Feng, Suo and Xiao, Yanghua [bib]
  

  liu-etal-2020-knowledge

• Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction ,
  by Hohenecker, Patrick and Mtumbuka, Frank and Kocijan, Vid and Lukasiewicz, Thomas [bib]
  

  hohenecker-etal-2020-systematic

• Hierarchical Evidence Set Modeling for Automated Fact Extraction and Verification ,
  by Subramanian, Shyam and Lee, Kyumin [bib]
  

  subramanian-lee-2020-hierarchical

• MedFilter: Improving Extraction of Task-relevant Utterances through Integration of Discourse Structure and Ontological Knowledge ,
  by Khosla, Sopan and Vashishth, Shikhar and Lehman, Jill Fain and Rose, Carolyn [bib]
  

  khosla-etal-2020-medfilter

• Domain Knowledge Empowered Structured Neural Net for End-to-End Event Temporal Relation Extraction ,
  by Han, Rujun and Zhou, Yichao and Peng, Nanyun [bib]
  

  han-etal-2020-domain

• OpenIE6: Iterative Grid Labeling and Coordination Analysis for Open Information Extraction ,
  by Kolluru, Keshav and Adlakha, Vaibhav and Aggarwal, Samarth and {Mausam} and Chakrabarti, Soumen [bib]
  

  kolluru-etal-2020-openie6

• Recurrent Interaction Network for Jointly Extracting Entities and Classifying Relations ,
  by Sun, Kai and Zhang, Richong and Mensah, Samuel and Mao, Yongyi and Liu, Xudong [bib]
  

  sun-etal-2020-recurrent

• Exposing Shallow Heuristics of Relation Extraction Models with Challenge Data ,
  by Rosenman, Shachar and Jacovi, Alon and Goldberg, Yoav [bib]
  

  rosenman-etal-2020-exposing

• Let's Stop Incorrect Comparisons in End-to-end Relation Extraction! ,
  by Taill{'e}, Bruno and Guigue, Vincent and Scoutheeten, Geoffrey and Gallinari, Patrick [bib]
  

  taille-etal-2020-lets

• Denoising Relation Extraction from Document-level Distant Supervision ,
  by Xiao, Chaojun and Yao, Yuan and Xie, Ruobing and Han, Xu and Liu, Zhiyuan and Sun, Maosong and Lin, Fen and Lin, Leyu [bib]
  

  xiao-etal-2020-denoising

• SelfORE: Self-supervised Relational Feature Learning for Open Relation Extraction ,
  by Hu, Xuming and Wen, Lijie and Xu, Yusong and Zhang, Chenwei and Yu, Philip [bib]
  

  hu-etal-2020-selfore

• Learning from Context or Names? An Empirical Study on Neural Relation Extraction ,
  by Peng, Hao and Gao, Tianyu and Han, Xu and Lin, Yankai and Li, Peng and Liu, Zhiyuan and Sun, Maosong and Zhou, Jie [bib]
  

  peng-etal-2020-learning

• An Information Bottleneck Approach for Controlling Conciseness in Rationale Extraction ,
  by Paranjape, Bhargavi and Joshi, Mandar and Thickstun, John and Hajishirzi, Hannaneh and Zettlemoyer, Luke [bib]
  

  paranjape-etal-2020-information

• Pre-training Entity Relation Encoder with Intra-span and Inter-span Information ,
  by Wang, Yijun and Sun, Changzhi and Wu, Yuanbin and Yan, Junchi and Gao, Peng and Xie, Guotong [bib]
  

  wang-etal-2020-pre

• Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders ,
  by Wang, Jue and Lu, Wei [bib]
  

  wang-lu-2020-two

• Event Extraction as Machine Reading Comprehension ,
  by Liu, Jian and Chen, Yubo and Liu, Kang and Bi, Wei and Liu, Xiaojiang [bib]
  

  liu-etal-2020-event

• Joint Constrained Learning for Event-Event Relation Extraction ,
  by Wang, Haoyu and Chen, Muhao and Zhang, Hongming and Roth, Dan [bib]
  

  wang-etal-2020-joint

• Event Extraction by Answering (Almost) Natural Questions ,
  by Du, Xinya and Cardie, Claire [bib]
  

  du-cardie-2020-event

• Coreferential Reasoning Learning for Language Representation ,
  by Deming Ye and Yankai Lin and Jiaju Du and Zhenghao Liu and Peng Li and Maosong Sun and Zhiyuan Liu [bib]
  

  YeLDLLSL20

• Double Graph Based Reasoning for Document-level Relation Extraction ,
  by Shuang Zeng and Runxin Xu and Baobao Chang and Lei Li [bib]
  

  ZengXCL20

• Global-to-Local Neural Networks for Document-Level Relation Extraction ,
  by Difeng Wang and Wei Hu and Ermei Cao and Weijian Sun [bib]
  

  WangHCS20

• FewRel 2.0: Towards More Challenging Few-Shot Relation Classification ,
  by Tianyu Gao and Xu Han and Hao Zhu and Zhiyuan Liu and Peng Li and Maosong Sun and Jie Zhou [bib] Fewrel 2.0 dataset
  

  GaoHZLLSZ19

• Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs ,
  by Fenia Christopoulou and Makoto Miwa and Sophia Ananiadou [bib]
  

  ChristopoulouMA19

• FewRel: A Large-Scale Supervised Few-shot Relation Classification Dataset with State-of-the-Art Evaluation ,
  by Xu Han and Hao Zhu and Pengfei Yu and Ziyun Wang and Yuan Yao and Zhiyuan Liu and Maosong Sun [bib] FewRel dataset
  

  HanZYWYLS18

• Modeling Joint Entity and Relation Extraction with Table Representation ,
  by Makoto Miwa and Yutaka Sasaki [bib]
  

  MiwaS14

• Kernel Methods for Relation Extraction ,
  by Dmitry Zelenko and Chinatsu Aone and Anthony Richardella [bib]
  

  ZelenkoAR02

NAACL

• Distantly Supervised Relation Extraction with Sentence Reconstruction and Knowledge Base Priors ,
  by Christopoulou, Fenia and Miwa, Makoto and Ananiadou, Sophia [bib]
  

  christopoulou-etal-2021-distantly

• A Frustratingly Easy Approach for Entity and Relation Extraction ,
  by Zhong, Zexuan and Chen, Danqi [bib]
  

  zhong-chen-2021-frustratingly

• ZS-BERT: Towards Zero-Shot Relation Extraction with Attribute Representation Learning ,
  by Chen, Chih-Yao and Li, Cheng-Te [bib]
  

  chen-li-2021-zs

• Jointly Extracting Explicit and Implicit Relational Triples with Reasoning Pattern Enhanced Binary Pointer Network ,
  by Chen, Yubo and Zhang, Yunqi and Hu, Changran and Huang, Yongfeng [bib]
  

  chen-etal-2021-jointly

• Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks ,
  by Nguyen, Minh Van and Lai, Viet and Nguyen, Thien Huu [bib]
  

  nguyen-etal-2021-cross

• Abstract Meaning Representation Guided Graph Encoding and Decoding for Joint Information Extraction ,
  by Zhang, Zixuan and Ji, Heng [bib]
  

  zhang-ji-2021-abstract

• Open Hierarchical Relation Extraction ,
  by Zhang, Kai and Yao, Yuan and Xie, Ruobing and Han, Xu and Liu, Zhiyuan and Lin, Fen and Lin, Leyu and Sun, Maosong [bib]
  

  zhang-etal-2021-open

• Document-Level Event Argument Extraction by Conditional Generation ,
  by Sha Li and Heng Ji and Jiawei Han [bib]
  

  LiJH21

COLING

• TPLinker: Single-stage Joint Extraction of Entities and Relations Through Token Pair Linking ,
  by Yucheng Wang and Bowen Yu and Yueyang Zhang and Tingwen Liu and Hongsong Zhu and Limin Sun [bib]
  

  WangYZLZS20

• Bridging Text and Knowledge with Multi-Prototype Embedding for Few-Shot Relational Triple Extraction ,
  by Haiyang Yu and Ningyu Zhang and Shumin Deng and Hongbin Ye and Wei Zhang and Huajun Chen [bib]
  

  YuZDYZC20

• Global Context-enhanced Graph Convolutional Networks for Document-level Relation Extraction ,
  by Huiwei Zhou and Yibin Xu and Weihong Yao and Zhe Liu and Chengkun Lang and Haibin Jiang [bib]
  

  ZhouXYLLJ20

• Document-level Relation Extraction with Dual-tier Heterogeneous Graph ,
  by Zhenyu Zhang and Bowen Yu and Xiaobo Shu and Tingwen Liu and Hengzhu Tang and Yubin Wang and Li Guo [bib]
  

  ZhangYSLTWG20

• Graph Enhanced Dual Attention Network for Document-Level Relation Extraction ,
  by Bo Li and Wei Ye and Zhonghao Sheng and Rui Xie and Xiangyu Xi and Shikun Zhang [bib]
  

  LiYSXXZ20

• Table Filling Multi-Task Recurrent Neural Network for Joint Entity and Relation Extraction ,
  by Pankaj Gupta and Hinrich Sch{"{u}}tze and Bernt Andrassy [bib]
  

  GuptaSA16

EACL

• Multilingual Entity and Relation Extraction Dataset and Model ,
  by Seganti, Alessandro and Firl{\k{a}}g, Klaudia and Skowronska, Helena and Sat{\l}awa, Micha{\l} and Andruszkiewicz, Piotr [bib]
  

  seganti-etal-2021-multilingual

• Learning Relatedness between Types with Prototypes for Relation Extraction ,
  by Fu, Lisheng and Grishman, Ralph [bib]
  

  fu-grishman-2021-learning

• ENPAR:Enhancing Entity and Entity Pair Representations for Joint Entity Relation Extraction ,
  by Wang, Yijun and Sun, Changzhi and Wu, Yuanbin and Zhou, Hao and Li, Lei and Yan, Junchi [bib]
  

  wang-etal-2021-enpar

• Modeling Coreference Relations in Visual Dialog ,
  by Li, Mingxiao and Moens, Marie-Francine [bib]
  

  li-moens-2021-modeling

• An End-to-end Model for Entity-level Relation Extraction using Multi-instance Learning ,
  by Eberts, Markus and Ulges, Adrian [bib]
  

  eberts-ulges-2021-end

• Two Training Strategies for Improving Relation Extraction over Universal Graph ,
  by Dai, Qin and Inoue, Naoya and Takahashi, Ryo and Inui, Kentaro [bib]
  

  dai-etal-2021-two

• An End-to-end Model for Entity-level Relation Extraction using Multi-instance Learning ,
  by Markus Eberts and Adrian Ulges [bib]
  

  EbertsU21

• GRIT: Generative Role-filler Transformers for Document-level Event Entity Extraction ,
  by Xinya Du and Alexander M. Rush and Claire Cardie [bib]
  

  DuRC21

• Bootstrapping Relation Extractors using Syntactic Search by Examples ,
  by Matan Eyal and Asaf Amrami and Hillel Taub{-}Tabib and Yoav Goldberg [bib]
  

  EyalATG21

AACL

• More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction ,
  by Xu Han and Tianyu Gao and Yankai Lin and Hao Peng and Yaoliang Yang and Chaojun Xiao and Zhiyuan Liu and Peng Li and Jie Zhou and Maosong Sun [bib]
  

  HanGLPYXLLZS20

ICML

• Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs ,
  by Qu, Meng, Gao, Tianyu, Xhonneux, Louis-Pascal and Tang, Jian [bib]
  

  pmlr-v119-qu20a

ICLR

• Prototypical Representation Learning for Relation Extraction ,
  by Ning Ding and Xiaobin Wang and Yao Fu and Guangwei Xu and Rui Wang and Pengjun Xie and Ying Shen and Fei Huang and Hai{-}Tao Zheng and Rui Zhang [bib]
  

  DingWFXWXSHZZ21

NeurIPS

• Knowledge Extraction with No Observable Data ,
  by Jaemin Yoo and Minyong Cho and Taebum Kim and U Kang [bib]
  

  YooCKK19

ECML

• Modeling Relations and Their Mentions without Labeled Text ,
  by Sebastian Riedel and Limin Yao and Andrew McCallum [bib]
  

  RiedelYM10

SIGIR

• Graph Learning Regularization and Transfer Learning for Few-Shot Event Detection ,
  by Lai, Viet Dac, Nguyen, Minh Van, Nguyen, Thien Huu and Dernoncourt, Franck [bib]
  

  3404835.3463054

KDD

• Knowledge-Enhanced Domain Adaptation in Few-Shot Relation Classification ,
  by Zhang, Jiawen, Zhu, Jiaqi, Yang, Yi, Shi, Wandong, Zhang, Congcong and Wang, Hongan [bib]
  

  3447548.3467438

AAAI

• FL-MSRE: A Few-Shot Learning based Approach to Multimodal Social Relation Extraction ,
  by Hai Wan and Manrong Zhang and Jianfeng Du and Ziling Huang and Yufei Yang and Jeff Z. Pan [bib] FL-MSRE
  

  WanZDHYP21

• Curriculum-Meta Learning for Order-Robust Continual Relation Extraction ,
  by Tongtong Wu and Xuekai Li and Yuan{-}Fang Li and Gholamreza Haffari and Guilin Qi and Yujin Zhu and Guoqiang Xu [bib]
  

  WuLLHQZX21

• Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling ,
  by Wenxuan Zhou and Kevin Huang and Tengyu Ma and Jing Huang [bib]
  

  Zhou0M021

• Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation Extraction ,
  by Benfeng Xu and Quan Wang and Yajuan Lyu and Yong Zhu and Zhendong Mao [bib]
  

  XuWLZM21

• Multi-view Inference for Relation Extraction with Uncertain Knowledge ,
  by Bo Li and Wei Ye and Canming Huang and Shikun Zhang [bib]
  

  LiYHZ21

• Document-Level Relation Extraction with Reconstruction ,
  by Wang Xu and Kehai Chen and Tiejun Zhao [bib]
  

  XuCZ21

• Neural Snowball for Few-Shot Relation Learning ,
  by Tianyu Gao and Xu Han and Ruobing Xie and Zhiyuan Liu and Fen Lin and Leyu Lin and Maosong Sun [bib] Neural Snowball
  

  GaoHX0LLS20

• Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification ,
  by Tianyu Gao and Xu Han and Zhiyuan Liu and Maosong Sun [bib] HATT
  

  GaoH0S19

IJCAI

• Document-level Relation Extraction as Semantic Segmentation ,
  by Zhang, Ningyu, Chen, Xiang, Xie, Xin, Deng, Shumin, Tan, Chuanqi, Chen, Mosha, Huang, Fei, Si, Luo and Chen, Huajun [bib]
  

  ijcai2021-551

• Consistent Inference for Dialogue Relation Extraction ,
  by Long, Xinwei, Niu, Shuzi and Li, Yucheng [bib]
  

  ijcai2021-535

ECAI

• Span-Based Joint Entity and Relation Extraction with Transformer Pre-Training ,
  by Markus Eberts and Adrian Ulges [bib]
  

  EbertsU20

WWW

• CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases ,
  by Xiang Ren and Zeqiu Wu and Wenqi He and Meng Qu and Clare R. Voss and Heng Ji and Tarek F. Abdelzaher and Jiawei Han [bib]
  

  RenWHQVJAH17

TACL

• Cross-A Large-Scale Document-Level RelatSentence N-ary Relation Extraction with Graph LSTMs ,
  by Nanyun Peng and Hoifung Poon and Chris Quirk and Kristina Toutanova and Wen{-}tau Yih [bib]
  

  PengPQTY17

ACM Comput. Surv.

• Relation Extraction Using Distant Supervision: A Survey ,
  by Alisa Smirnova and Philippe Cudr{'{e}}{-}Mauroux [bib] SmirnovaC19
  

  SmirnovaC19

NUSE-NAACL

• Document-level Event Extraction with Efficient End-to-end Learning of Cross-event Dependencies ,
  by Huang, Kung-Hsiang and Peng, Nanyun [bib]
  

  huang-peng-2021-document

arXiv

• AdaPrompt: Adaptive Prompt-based Finetuning for Relation Extraction ,
  by Xiang Chen and Xin Xie and Ningyu Zhang and Jiahuan Yan and Shumin Deng and Chuanqi Tan and Fei Huang and Luo Si and Huajun Chen [bib]
  

  abs-2104-07650

• Event Extraction as Natural Language Generation ,
  by I-Hung Hsu, Kuan-Hao Huang, Elizabeth Boschee, Scott Miller, Prem Natarajan, Kai-Wei Chang and Nanyun Peng [bib]
  

  hsu2021event

• Entity and Evidence Guided Relation Extraction for DocRED ,
  by Kevin Huang and Guangtao Wang and Tengyu Ma and Jing Huang [bib]
  

  abs-2008-12283

• Fine-tune Bert for DocRED with Two-step Process ,
  by Hong Wang and Christfried Focke and Rob Sylvester and Nilesh Mishra and William Yang Wang [bib]
  

  abs-1909-11898