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Awesome_Information_Extraction

Literature Survey of Information Extraction, especially Relation Extraction, Event Extraction, and Slot Filling.
https://github.com/wutong8023/Awesome_Information_Extraction

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  • ![ - long.395)<a href="https://scholar.google.com.hk/scholar?q=Unified+Structure+Generation+for+Universal+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Unified Structure Generation for Universal Information Extraction**](https://aclanthology.org/2022.acl-long.395) , <br> by *Lu, Yaojie and
  • ![ - short.26)<a href="https://scholar.google.com.hk/scholar?q=Event-Event+Relation+Extraction+using+Probabilistic+Box+Embedding"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Event-Event Relation Extraction using Probabilistic Box Embedding**](https://aclanthology.org/2022.acl-short.26) , <br> by *Hwang, EunJeong and
  • ![ - long.466)<a href="https://scholar.google.com.hk/scholar?q=Prompt+for+Extraction?+PAIE:+Prompting+Argument+Interaction+for+Event+Argument+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction**](https://aclanthology.org/2022.acl-long.466) , <br> by *Ma, Yubo and
  • ![ - long.313)<a href="https://scholar.google.com.hk/scholar?q=Saliency+as+Evidence:+Event+Detection+with+Trigger+Saliency+Attribution"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Saliency as Evidence: Event Detection with Trigger Saliency Attribution**](https://aclanthology.org/2022.acl-long.313) , <br> by *Liu, Jian and
  • ![ - long.317)<a href="https://scholar.google.com.hk/scholar?q=Multilingual+Generative+Language+Models+for+Zero-Shot+Cross-Lingual+Event+Argument+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction**](https://aclanthology.org/2022.acl-long.317) , <br> by *Huang, Kuan-Hao and
  • ![ - long.216)<a href="https://scholar.google.com.hk/scholar?q=Improving+Event+Representation+via+Simultaneous+Weakly+Supervised+Contrastive+Learning+and+Clustering"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Improving Event Representation via Simultaneous Weakly Supervised Contrastive Learning and Clustering**](https://aclanthology.org/2022.acl-long.216) , <br> by *Gao, Jun and
  • ![ - long.358)<a href="https://scholar.google.com.hk/scholar?q=Dynamic+Prefix-Tuning+for+Generative+Template-based+Event+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Dynamic Prefix-Tuning for Generative Template-based Event Extraction**](https://aclanthology.org/2022.acl-long.358) , <br> by *Liu, Xiao and
  • ![ - long.361)<a href="https://scholar.google.com.hk/scholar?q=Dynamic+Global+Memory+for+Document-level+Argument+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Dynamic Global Memory for Document-level Argument Extraction**](https://aclanthology.org/2022.acl-long.361) , <br> by *Du, Xinya and
  • ![ - long.274)<a href="https://scholar.google.com.hk/scholar?q=Automatic+Error+Analysis+for+Document-level+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Automatic Error Analysis for Document-level Information Extraction**](https://aclanthology.org/2022.acl-long.274) , <br> by *Das, Aliva and
  • ![ - long.183)<a href="https://scholar.google.com.hk/scholar?q=ClarET:+Pre-training+a+Correlation-Aware+Context-To-Event+Transformer+for+Event-Centric+Generation+and+Classification"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification**](https://aclanthology.org/2022.acl-long.183) , <br> by *Zhou, Yucheng and
  • ![ - long.337)<a href="https://scholar.google.com.hk/scholar?q=Packed+Levitated+Marker+for+Entity+and+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Packed Levitated Marker for Entity and Relation Extraction**](https://aclanthology.org/2022.acl-long.337) , <br> by *Ye, Deming and
  • ![ - long.410)<a href="https://scholar.google.com.hk/scholar?q=Learning+to+Reason+Deductively:+Math+Word+Problem+Solving+as+Complex+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction**](https://aclanthology.org/2022.acl-long.410) , <br> by *Jie, Zhanming and
  • ![ - long.397)<a href="https://scholar.google.com.hk/scholar?q=Pre-training+to+Match+for+Unified+Low-shot+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Pre-training to Match for Unified Low-shot Relation Extraction**](https://aclanthology.org/2022.acl-long.397) , <br> by *Liu, Fangchao and
  • ![ - short.38)<a href="https://scholar.google.com.hk/scholar?q=PARE:+A+Simple+and+Strong+Baseline+for+Monolingual+and+Multilingual+Distantly+Supervised+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**PARE: A Simple and Strong Baseline for Monolingual and Multilingual Distantly Supervised Relation Extraction**](https://aclanthology.org/2022.acl-short.38) , <br> by *Rathore, Vipul and
  • ![ - acl.214)<a href="https://scholar.google.com.hk/scholar?q=Adaptive+Knowledge-Enhanced+Bayesian+Meta-Learning+for+Few-shot+Event+Detection"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Adaptive Knowledge-Enhanced Bayesian Meta-Learning for Few-shot Event
  • ![ - long.492)<a href="https://scholar.google.com.hk/scholar?q=Document-level+Event+Extraction+via+Parallel+Prediction+Networks"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Document-level Event Extraction via Parallel Prediction Networks**](https://aclanthology.org/2021.acl-long.492) , <br> by *Yang, Hang and
  • ![ - long.491)<a href="https://scholar.google.com.hk/scholar?q=CLEVE:+Contrastive+Pre-training+for+Event+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**CLEVE: Contrastive Pre-training for Event Extraction**](https://aclanthology.org/2021.acl-long.491) , <br> by *Wang, Ziqi and
  • ![ - long.486)<a href="https://scholar.google.com.hk/scholar?q=PRGC:+Potential+Relation+and+Global+Correspondence+Based+Joint+Relational+Triple+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**PRGC: Potential Relation and Global Correspondence Based Joint Relational Triple Extraction**](https://aclanthology.org/2021.acl-long.486) , <br> by *Zheng, Hengyi and
  • ![ - short.67)<a href="https://scholar.google.com.hk/scholar?q=TIMERS:+Document-level+Temporal+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**TIMERS: Document-level Temporal Relation Extraction**](https://aclanthology.org/2021.acl-short.67) , <br> by *Mathur, Puneet and
  • ![ - long.248)<a href="https://scholar.google.com.hk/scholar?q=Few-NERD:+A+Few-shot+Named+Entity+Recognition+Dataset"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Few-NERD: A Few-shot Named Entity Recognition Dataset**](https://aclanthology.org/2021.acl-long.248) , <br> by *Ding, Ning and
  • ![ - long.496)<a href="https://scholar.google.com.hk/scholar?q=Argument+Pair+Extraction+via+Attention-guided+Multi-Layer+Multi-Cross+Encoding"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Argument Pair Extraction via Attention-guided Multi-Layer Multi-Cross Encoding**](https://aclanthology.org/2021.acl-long.496) , <br> by *Cheng, Liying and
  • ![ - long.19)<a href="https://scholar.google.com.hk/scholar?q=UniRE:+A+Unified+Label+Space+for+Entity+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**UniRE: A Unified Label Space for Entity Relation Extraction**](https://aclanthology.org/2021.acl-long.19) , <br> by *Wang, Yijun and
  • ![ - short.118)<a href="https://scholar.google.com.hk/scholar?q=Addressing+Semantic+Drift+in+Generative+Question+Answering+with+Auxiliary+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Addressing Semantic Drift in Generative Question Answering with Auxiliary Extraction**](https://aclanthology.org/2021.acl-short.118) , <br> by *Li, Chenliang and
  • ![ - long.20)<a href="https://scholar.google.com.hk/scholar?q=Refining+Sample+Embeddings+with+Relation+Prototypes+to+Enhance+Continual+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Refining Sample Embeddings with Relation Prototypes to Enhance Continual Relation Extraction**](https://aclanthology.org/2021.acl-long.20) , <br> by *Cui, Li and
  • ![ - short.124)<a href="https://scholar.google.com.hk/scholar?q=Entity+Concept-enhanced+Few-shot+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Entity Concept-enhanced Few-shot Relation Extraction**](https://aclanthology.org/2021.acl-short.124) , <br> by *Yang, Shan and
  • ![ - long.217)<a href="https://scholar.google.com.hk/scholar?q=Text2Event:+Controllable+Sequence-to-Structure+Generation+for+End-to-end+Event+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction**](https://aclanthology.org/2021.acl-long.217) , <br> by *Lu, Yaojie and
  • ![ - long.344)<a href="https://scholar.google.com.hk/scholar?q=Dependency-driven+Relation+Extraction+with+Attentive+Graph+Convolutional+Networks"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Dependency-driven Relation Extraction with Attentive Graph Convolutional Networks**](https://aclanthology.org/2021.acl-long.344) , <br> by *Tian, Yuanhe and
  • ![ - long.146)<a href="https://scholar.google.com.hk/scholar?q=Knowledgeable+or+Educated+Guess?+Revisiting+Language+Models+as+Knowledge+Bases"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Knowledgeable or Educated Guess? Revisiting Language Models as Knowledge Bases**](https://aclanthology.org/2021.acl-long.146) , <br> by *Cao, Boxi and
  • ![ - long.359)<a href="https://scholar.google.com.hk/scholar?q=How+Knowledge+Graph+and+Attention+Help?+A+Qualitative+Analysis+into+Bag-level+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**How Knowledge Graph and Attention Help? A Qualitative Analysis into Bag-level Relation Extraction**](https://aclanthology.org/2021.acl-long.359) , <br> by *Hu, Zikun and
  • ![ - long.360)<a href="https://scholar.google.com.hk/scholar?q=Trigger+is+Not+Sufficient:+Exploiting+Frame-aware+Knowledge+for+Implicit+Event+Argument+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Trigger is Not Sufficient: Exploiting Frame-aware Knowledge for Implicit Event Argument Extraction**](https://aclanthology.org/2021.acl-long.360) , <br> by *Wei, Kaiwen and
  • ![ - long.361)<a href="https://scholar.google.com.hk/scholar?q=Element+Intervention+for+Open+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Element Intervention for Open Relation Extraction**](https://aclanthology.org/2021.acl-long.361) , <br> by *Liu, Fangchao and
  • ![ - long.363)<a href="https://scholar.google.com.hk/scholar?q=CoRI:+Collective+Relation+Integration+with+Data+Augmentation+for+Open+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**CoRI: Collective Relation Integration with Data Augmentation for Open Information Extraction**](https://aclanthology.org/2021.acl-long.363) , <br> by *Jiang, Zhengbao and
  • ![ - long.274)<a href="https://scholar.google.com.hk/scholar?q=Document-level+Event+Extraction+via+Heterogeneous+Graph-based+Interaction+Model+with+a+Tracker"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker**](https://aclanthology.org/2021.acl-long.274) , <br> by *Xu, Runxin and
  • ![ - long.277)<a href="https://scholar.google.com.hk/scholar?q=Revisiting+the+Negative+Data+of+Distantly+Supervised+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Revisiting the Negative Data of Distantly Supervised Relation Extraction**](https://aclanthology.org/2021.acl-long.277) , <br> by *Xie, Chenhao and
  • ![ - long.488)<a href="https://scholar.google.com.hk/scholar?q=Joint+Biomedical+Entity+and+Relation+Extraction+with+Knowledge-Enhanced+Collective+Inference"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Joint Biomedical Entity and Relation Extraction with Knowledge-Enhanced Collective Inference**](https://aclanthology.org/2021.acl-long.488) , <br> by *Lai, Tuan and
  • ![ - long.484)<a href="https://scholar.google.com.hk/scholar?q=SENT:+Sentence-level+Distant+Relation+Extraction+via+Negative+Training"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**SENT: Sentence-level Distant Relation Extraction via Negative Training**](https://aclanthology.org/2021.acl-long.484) , <br> by *Ma, Ruotian and
  • ![ - long.375)<a href="https://scholar.google.com.hk/scholar?q=StereoRel:+Relational+Triple+Extraction+from+a+Stereoscopic+Perspective"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**StereoRel: Relational Triple Extraction from a Stereoscopic Perspective**](https://aclanthology.org/2021.acl-long.375) , <br> by *Tian, Xuetao and
  • ![ - long.483)<a href="https://scholar.google.com.hk/scholar?q=CIL:+Contrastive+Instance+Learning+Framework+for+Distantly+Supervised+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**CIL: Contrastive Instance Learning Framework for Distantly Supervised Relation Extraction**](https://aclanthology.org/2021.acl-long.483) , <br> by *Chen, Tao and
  • ![ - long.60)<a href="https://scholar.google.com.hk/scholar?q=From+Discourse+to+Narrative:+Knowledge+Projection+for+Event+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**From Discourse to Narrative: Knowledge Projection for Event Relation Extraction**](https://aclanthology.org/2021.acl-long.60) , <br> by *Tang, Jialong and
  • ![ - short.42)<a href="https://scholar.google.com.hk/scholar?q=Zero-shot+Event+Extraction+via+Transfer+Learning:+Challenges+and+Insights"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Zero-shot Event Extraction via Transfer Learning: Challenges and Insights**](https://aclanthology.org/2021.acl-short.42) , <br> by *Lyu, Qing and
  • ![ - short.41)<a href="https://scholar.google.com.hk/scholar?q=ROPE:+Reading+Order+Equivariant+Positional+Encoding+for+Graph-based+Document+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction**](https://aclanthology.org/2021.acl-short.41) , <br> by *Lee, Chen-Yu and
  • ![ - short.126)<a href="https://scholar.google.com.hk/scholar?q=Three+Sentences+Are+All+You+Need:+Local+Path+Enhanced+Document+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Three Sentences Are All You Need: Local Path Enhanced Document Relation Extraction**](https://aclanthology.org/2021.acl-short.126) , <br> by *Huang, Quzhe and
  • ![ - main.713)<a href="https://scholar.google.com.hk/scholar?q=A+Joint+Neural+Model+for+Information+Extraction+with+Global+Features"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**A Joint Neural Model for Information Extraction with Global Features**](https://aclanthology.org/2020.acl-main.713) , <br> by *Lin, Ying and
  • ![ - main.751)<a href="https://scholar.google.com.hk/scholar?q=TXtract:+Taxonomy-Aware+Knowledge+Extraction+for+Thousands+of+Product+Categories"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**TXtract: Taxonomy-Aware Knowledge Extraction for Thousands of Product Categories**](https://www.aclweb.org/anthology/2020.acl-main.751) , <br> by *Karamanolakis, Giannis and
  • ![ - main.721)<a href="https://scholar.google.com.hk/scholar?q=ZeroShotCeres:+Zero-Shot+Relation+Extraction+from+Semi-Structured+Webpages"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**ZeroShotCeres: Zero-Shot Relation Extraction from Semi-Structured Webpages**](https://www.aclweb.org/anthology/2020.acl-main.721) , <br> by *Lockard, Colin and
  • ![ - main.715)<a href="https://scholar.google.com.hk/scholar?q=Exploiting+the+Syntax-Model+Consistency+for+Neural+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Exploiting the Syntax-Model Consistency for Neural Relation Extraction**](https://www.aclweb.org/anthology/2020.acl-main.715) , <br> by *Pouran Ben Veyseh, Amir and
  • ![ - main.670)<a href="https://scholar.google.com.hk/scholar?q=SciREX:+A+Challenge+Dataset+for+Document-Level+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**SciREX: A Challenge Dataset for Document-Level Information Extraction**](https://www.aclweb.org/anthology/2020.acl-main.670) , <br> by *Jain, Sarthak and
  • ![ - main.669)<a href="https://scholar.google.com.hk/scholar?q=Revisiting+Unsupervised+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Revisiting Unsupervised Relation Extraction**](https://www.aclweb.org/anthology/2020.acl-main.669) , <br> by *Tran, Thy Thy and
  • ![ - main.579)<a href="https://scholar.google.com.hk/scholar?q=Relation+Extraction+with+Explanation"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Relation Extraction with Explanation**](https://www.aclweb.org/anthology/2020.acl-main.579) , <br> by *Shahbazi, Hamed and
  • ![ - main.527)<a href="https://scholar.google.com.hk/scholar?q=Relabel+the+Noise:+Joint+Extraction+of+Entities+and+Relations+via+Cooperative+Multiagents"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Relabel the Noise: Joint Extraction of Entities and Relations via Cooperative Multiagents**](https://www.aclweb.org/anthology/2020.acl-main.527) , <br> by *Chen, Daoyuan and
  • ![ - main.521)<a href="https://scholar.google.com.hk/scholar?q=IMoJIE:+Iterative+Memory-Based+Joint+Open+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**IMoJIE: Iterative Memory-Based Joint Open Information Extraction**](https://www.aclweb.org/anthology/2020.acl-main.521) , <br> by *Kolluru, Keshav and
  • ![ - main.444)<a href="https://scholar.google.com.hk/scholar?q=Dialogue-Based+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Dialogue-Based Relation Extraction**](https://www.aclweb.org/anthology/2020.acl-main.444) , <br> by *Yu, Dian and
  • ![ - main.230)<a href="https://scholar.google.com.hk/scholar?q=Cross-media+Structured+Common+Space+for+Multimedia+Event+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Cross-media Structured Common Space for Multimedia Event Extraction**](https://www.aclweb.org/anthology/2020.acl-main.230) , <br> by *Li, Manling and
  • ![ - main.142)<a href="https://scholar.google.com.hk/scholar?q=TACRED+Revisited:+A+Thorough+Evaluation+of+the+TACRED+Relation+Extraction+Task"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**TACRED Revisited: A Thorough Evaluation of the TACRED Relation Extraction Task**](https://www.aclweb.org/anthology/2020.acl-main.142) , <br> by *Alt, Christoph and
  • ![ - main.140)<a href="https://scholar.google.com.hk/scholar?q=Probing+Linguistic+Features+of+Sentence-Level+Representations+in+Neural+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Probing Linguistic Features of Sentence-Level Representations in Neural Relation Extraction**](https://www.aclweb.org/anthology/2020.acl-main.140) , <br> by *Alt, Christoph and
  • ![ - main.139)<a href="https://scholar.google.com.hk/scholar?q=Named+Entity+Recognition+without+Labelled+Data:+A+Weak+Supervision+Approach"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Named Entity Recognition without Labelled Data: A Weak Supervision Approach**](https://www.aclweb.org/anthology/2020.acl-main.139) , <br> by *Lison, Pierre and
  • ![ - main.137)<a href="https://scholar.google.com.hk/scholar?q=In+Layman's+Terms:+Semi-Open+Relation+Extraction+from+Scientific+Texts"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**In Layman's Terms: Semi-Open Relation Extraction from Scientific Texts**](https://www.aclweb.org/anthology/2020.acl-main.137) , <br> by *Kruiper, Ruben and
  • ![ - main.136)<a href="https://scholar.google.com.hk/scholar?q=A+Novel+Cascade+Binary+Tagging+Framework+for+Relational+Triple+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**A Novel Cascade Binary Tagging Framework for Relational Triple Extraction**](https://www.aclweb.org/anthology/2020.acl-main.136) , <br> by *Wei, Zhepei and
  • ![ - main.714)<a href="https://scholar.google.com.hk/scholar?q=Document-Level+Event+Role+Filler+Extraction+using+Multi-Granularity+Contextualized+Encoding"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Document-Level Event Role Filler Extraction using Multi-Granularity
  • ![ - main.718)<a href="https://scholar.google.com.hk/scholar?q=Multi-Sentence+Argument+Linking"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Multi-Sentence Argument Linking**](https://doi.org/10.18653/v1/2020.acl-main.718) , <br> by *Seth Ebner and
  • ![ - main.141)<a href="https://scholar.google.com.hk/scholar?q=Reasoning+with+Latent+Structure+Refinement+for+Document-Level+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Reasoning with Latent Structure Refinement for Document-Level Relation
  • ![ - main.667)<a href="https://scholar.google.com.hk/scholar?q=A+Two-Step+Approach+for+Implicit+Event+Argument+Detection"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**A Two-Step Approach for Implicit Event Argument Detection**](https://doi.org/10.18653/v1/2020.acl-main.667) , <br> by *Zhisong Zhang and
  • ![ - 1136)<a href="https://scholar.google.com.hk/scholar?q=GraphRel:+Modeling+Text+as+Relational+Graphs+for+Joint+Entity+and+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction**](https://doi.org/10.18653/v1/p19-1136) , <br> by *Tsu{-}Jui Fu and
  • ![ - 1128)<a href="https://scholar.google.com.hk/scholar?q=Graph+Neural+Networks+with+Generated+Parameters+for+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Graph Neural Networks with Generated Parameters for Relation Extraction**](https://doi.org/10.18653/v1/p19-1128) , <br> by *Hao Zhu and
  • ![ - 1279)<a href="https://scholar.google.com.hk/scholar?q=Matching+the+Blanks:+Distributional+Similarity+for+Relation+Learning"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Matching the Blanks: Distributional Similarity for Relation Learning**](https://doi.org/10.18653/v1/p19-1279) , <br> by *Livio Baldini Soares and
  • ![ - 1277)<a href="https://scholar.google.com.hk/scholar?q=Multi-Level+Matching+and+Aggregation+Network+for+Few-Shot+Relation+Classification"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Multi-Level Matching and Aggregation Network for Few-Shot Relation
  • ![ - 1074)<a href="https://scholar.google.com.hk/scholar?q=DocRED:+A+Large-Scale+Document-Level+Relation+Extraction+Dataset"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**DocRED: A Large-Scale Document-Level Relation Extraction Dataset**](https://www.aclweb.org/anthology/P19-1074) , <br> by *Yao, Yuan and
  • ![ - 1047/)<a href="https://scholar.google.com.hk/scholar?q=Extracting+Relational+Facts+by+an+End-to-End+Neural+Model+with+Copy+Mechanism"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Extracting Relational Facts by an End-to-End Neural Model with Copy
  • ![ - 1017)<a href="https://scholar.google.com.hk/scholar?q=Creating+Training+Corpora+for+NLG+Micro-Planners"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Creating Training Corpora for NLG Micro-Planners**](https://doi.org/10.18653/v1/P17-1017) , <br> by *Claire Gardent and
  • ![ - 5010)<a href="https://scholar.google.com.hk/scholar?q=The+Stanford+CoreNLP+Natural+Language+Processing+Toolkit"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**The Stanford CoreNLP Natural Language Processing Toolkit**](https://doi.org/10.3115/v1/p14-5010) , <br> by *Christopher D. Manning and
  • ![ - 1038)<a href="https://scholar.google.com.hk/scholar?q=Incremental+Joint+Extraction+of+Entity+Mentions+and+Relations"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Incremental Joint Extraction of Entity Mentions and Relations**](https://doi.org/10.3115/v1/p14-1038) , <br> by *Qi Li and
  • ![ - 1056/)<a href="https://scholar.google.com.hk/scholar?q=Exploiting+Syntactico-Semantic+Structures+for+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Exploiting Syntactico-Semantic Structures for Relation Extraction**](https://aclanthology.org/P11-1056/) , <br> by *Yee Seng Chan and
  • ![ - 1053/)<a href="https://scholar.google.com.hk/scholar?q=Exploring+Various+Knowledge+in+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Exploring Various Knowledge in Relation Extraction**](https://aclanthology.org/P05-1053/) , <br> by *Guodong Zhou and
  • ![ - main.366)<a href="https://scholar.google.com.hk/scholar?q=CodRED:+A+Cross-Document+Relation+Extraction+Dataset+for+Acquiring+Knowledge+in+the+Wild"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**CodRED: A Cross-Document Relation Extraction Dataset for Acquiring Knowledge in the Wild**](https://aclanthology.org/2021.emnlp-main.366) , <br> by *Yao, Yuan and
  • ![ - main.95)<a href="https://scholar.google.com.hk/scholar?q=Learning+Logic+Rules+for+Document-Level+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Learning Logic Rules for Document-Level Relation Extraction**](https://aclanthology.org/2021.emnlp-main.95) , <br> by *Ru, Dongyu and
  • ![ - main.94)<a href="https://scholar.google.com.hk/scholar?q=Zero-Shot+Information+Extraction+as+a+Unified+Text-to-Triple+Translation"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Zero-Shot Information Extraction as a Unified Text-to-Triple Translation**](https://aclanthology.org/2021.emnlp-main.94) , <br> by *Wang, Chenguang and
  • ![ - main.763)<a href="https://scholar.google.com.hk/scholar?q=Uncovering+Main+Causalities+for+Long-tailed+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Uncovering Main Causalities for Long-tailed Information Extraction**](https://aclanthology.org/2021.emnlp-main.763) , <br> by *Nan, Guoshun and
  • ![ - main.765)<a href="https://scholar.google.com.hk/scholar?q=A+Relation-Oriented+Clustering+Method+for+Open+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**A Relation-Oriented Clustering Method for Open Relation Extraction**](https://aclanthology.org/2021.emnlp-main.765) , <br> by *Zhao, Jun and
  • ![ - main.816)<a href="https://scholar.google.com.hk/scholar?q=Separating+Retention+from+Extraction+in+the+Evaluation+of+End-to-end+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Separating Retention from Extraction in the Evaluation of End-to-end Relation Extraction**](https://aclanthology.org/2021.emnlp-main.816) , <br> by *Taill{\'e}, Bruno and
  • ![ - main.635)<a href="https://scholar.google.com.hk/scholar?q=TDEER:+An+Efficient+Translating+Decoding+Schema+for+Joint+Extraction+of+Entities+and+Relations"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**TDEER: An Efficient Translating Decoding Schema for Joint Extraction of Entities and Relations**](https://aclanthology.org/2021.emnlp-main.635) , <br> by *Li, Xianming and
  • ![ - main.204)<a href="https://scholar.google.com.hk/scholar?q=Exploring+Task+Difficulty+for+Few-Shot+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Exploring Task Difficulty for Few-Shot Relation Extraction**](https://aclanthology.org/2021.emnlp-main.204) , <br> by *Han, Jiale and
  • ![ - main.208)<a href="https://scholar.google.com.hk/scholar?q=A+Novel+Global+Feature-Oriented+Relational+Triple+Extraction+Model+based+on+Table+Filling"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**A Novel Global Feature-Oriented Relational Triple Extraction Model based on Table Filling**](https://aclanthology.org/2021.emnlp-main.208) , <br> by *Ren, Feiliang and
  • ![ - main.426)<a href="https://scholar.google.com.hk/scholar?q=Document-level+Entity-based+Extraction+as+Template+Generation"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Document-level Entity-based Extraction as Template Generation**](https://aclanthology.org/2021.emnlp-main.426) , <br> by *Huang, Kung-Hsiang and
  • ![ - main.429)<a href="https://scholar.google.com.hk/scholar?q=Modular+Self-Supervision+for+Document-Level+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Modular Self-Supervision for Document-Level Relation Extraction**](https://aclanthology.org/2021.emnlp-main.429) , <br> by *Zhang, Sheng and
  • ![ - main.212)<a href="https://scholar.google.com.hk/scholar?q=MapRE:+An+Effective+Semantic+Mapping+Approach+for+Low-resource+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**MapRE: An Effective Semantic Mapping Approach for Low-resource Relation Extraction**](https://aclanthology.org/2021.emnlp-main.212) , <br> by *Dong, Manqing and
  • ![ - main.214)<a href="https://scholar.google.com.hk/scholar?q=Machine+Reading+Comprehension+as+Data+Augmentation:+A+Case+Study+on+Implicit+Event+Argument+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Machine Reading Comprehension as Data Augmentation: A Case Study on Implicit Event Argument Extraction**](https://aclanthology.org/2021.emnlp-main.214) , <br> by *Liu, Jian and
  • ![ - main.433)<a href="https://scholar.google.com.hk/scholar?q=Towards+Realistic+Few-Shot+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Towards Realistic Few-Shot Relation Extraction**](https://aclanthology.org/2021.emnlp-main.433) , <br> by *Brody, Sam and
  • ![ - main.216)<a href="https://scholar.google.com.hk/scholar?q=Gradient+Imitation+Reinforcement+Learning+for+Low+Resource+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Gradient Imitation Reinforcement Learning for Low Resource Relation Extraction**](https://aclanthology.org/2021.emnlp-main.216) , <br> by *Hu, Xuming and
  • ![ - main.435)<a href="https://scholar.google.com.hk/scholar?q=Incorporating+medical+knowledge+in+BERT+for+clinical+relation+extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Incorporating medical knowledge in BERT for clinical relation extraction**](https://aclanthology.org/2021.emnlp-main.435) , <br> by *Roy, Arpita and
  • ![ - main.218)<a href="https://scholar.google.com.hk/scholar?q=Entity+Relation+Extraction+as+Dependency+Parsing+in+Visually+Rich+Documents"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Entity Relation Extraction as Dependency Parsing in Visually Rich Documents**](https://aclanthology.org/2021.emnlp-main.218) , <br> by *Zhang, Yue and
  • ![ - main.219)<a href="https://scholar.google.com.hk/scholar?q=Synchronous+Dual+Network+with+Cross-Type+Attention+for+Joint+Entity+and+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Synchronous Dual Network with Cross-Type Attention for Joint Entity and Relation Extraction**](https://aclanthology.org/2021.emnlp-main.219) , <br> by *Wu, Hui and
  • ![ - main.437)<a href="https://scholar.google.com.hk/scholar?q=Learning+from+Noisy+Labels+for+Entity-Centric+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Learning from Noisy Labels for Entity-Centric Information Extraction**](https://aclanthology.org/2021.emnlp-main.437) , <br> by *Zhou, Wenxuan and
  • ![ - main.440)<a href="https://scholar.google.com.hk/scholar?q=Crosslingual+Transfer+Learning+for+Relation+and+Event+Extraction+via+Word+Category+and+Class+Alignments"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Crosslingual Transfer Learning for Relation and Event Extraction via Word Category and Class Alignments**](https://aclanthology.org/2021.emnlp-main.440) , <br> by *Nguyen, Minh Van and
  • ![ - main.228)<a href="https://scholar.google.com.hk/scholar?q=Relation+Extraction+with+Word+Graphs+from+N-grams"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Relation Extraction with Word Graphs from N-grams**](https://aclanthology.org/2021.emnlp-main.228) , <br> by *Qin, Han and
  • ![ - main.146)<a href="https://scholar.google.com.hk/scholar?q=AttentionRank:+Unsupervised+Keyphrase+Extraction+using+Self+and+Cross+Attentions"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**AttentionRank: Unsupervised Keyphrase Extraction using Self and Cross Attentions**](https://aclanthology.org/2021.emnlp-main.146) , <br> by *Ding, Haoran and
  • ![ - main.14)<a href="https://scholar.google.com.hk/scholar?q=Unsupervised+Keyphrase+Extraction+by+Jointly+Modeling+Local+and+Global+Context"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Unsupervised Keyphrase Extraction by Jointly Modeling Local and Global Context**](https://aclanthology.org/2021.emnlp-main.14) , <br> by *Liang, Xinnian and
  • ![ - main.147)<a href="https://scholar.google.com.hk/scholar?q=Unsupervised+Relation+Extraction:+A+Variational+Autoencoder+Approach"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Unsupervised Relation Extraction: A Variational Autoencoder Approach**](https://aclanthology.org/2021.emnlp-main.147) , <br> by *Yuan, Chenhan and
  • ![ - main.149)<a href="https://scholar.google.com.hk/scholar?q=Everything+Is+All+It+Takes:+A+Multipronged+Strategy+for+Zero-Shot+Cross-Lingual+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction**](https://aclanthology.org/2021.emnlp-main.149) , <br> by *Yarmohammadi, Mahsa and
  • ![ - main.17)<a href="https://scholar.google.com.hk/scholar?q=A+Partition+Filter+Network+for+Joint+Entity+and+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**A Partition Filter Network for Joint Entity and Relation Extraction**](https://aclanthology.org/2021.emnlp-main.17) , <br> by *Yan, Zhiheng and
  • ![ - main.171)<a href="https://scholar.google.com.hk/scholar?q=Generation+and+Extraction+Combined+Dialogue+State+Tracking+with+Hierarchical+Ontology+Integration"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Generation and Extraction Combined Dialogue State Tracking with Hierarchical Ontology Integration**](https://aclanthology.org/2021.emnlp-main.171) , <br> by *Li, Xinmeng and
  • ![ - main.271)<a href="https://scholar.google.com.hk/scholar?q=Cost-effective+End-to-end+Information+Extraction+for+Semi-structured+Document+Images"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Cost-effective End-to-end Information Extraction for Semi-structured Document Images**](https://aclanthology.org/2021.emnlp-main.271) , <br> by *Hwang, Wonseok and
  • ![ - main.129)<a href="https://scholar.google.com.hk/scholar?q=MAVEN:+A+Massive+General+Domain+Event+Detection+Dataset"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**MAVEN: A Massive General Domain Event Detection Dataset**](https://www.aclweb.org/anthology/2020.emnlp-main.129) , <br> by *Wang, Xiaozhi and
  • ![ - main.693)<a href="https://scholar.google.com.hk/scholar?q=Knowledge-guided+Open+Attribute+Value+Extraction+with+Reinforcement+Learning"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Knowledge-guided Open Attribute Value Extraction with Reinforcement Learning**](https://www.aclweb.org/anthology/2020.emnlp-main.693) , <br> by *Liu, Ye and
  • ![ - main.690)<a href="https://scholar.google.com.hk/scholar?q=Systematic+Comparison+of+Neural+Architectures+and+Training+Approaches+for+Open+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction**](https://www.aclweb.org/anthology/2020.emnlp-main.690) , <br> by *Hohenecker, Patrick and
  • ![ - main.627)<a href="https://scholar.google.com.hk/scholar?q=Hierarchical+Evidence+Set+Modeling+for+Automated+Fact+Extraction+and+Verification"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Hierarchical Evidence Set Modeling for Automated Fact Extraction and Verification**](https://www.aclweb.org/anthology/2020.emnlp-main.627) , <br> by *Subramanian, Shyam and
  • ![ - main.626)<a href="https://scholar.google.com.hk/scholar?q=MedFilter:+Improving+Extraction+of+Task-relevant+Utterances+through+Integration+of+Discourse+Structure+and+Ontological+Knowledge"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**MedFilter: Improving Extraction of Task-relevant Utterances through Integration of Discourse Structure and Ontological Knowledge**](https://www.aclweb.org/anthology/2020.emnlp-main.626) , <br> by *Khosla, Sopan and
  • ![ - main.461)<a href="https://scholar.google.com.hk/scholar?q=Domain+Knowledge+Empowered+Structured+Neural+Net+for+End-to-End+Event+Temporal+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Domain Knowledge Empowered Structured Neural Net for End-to-End Event Temporal Relation Extraction**](https://www.aclweb.org/anthology/2020.emnlp-main.461) , <br> by *Han, Rujun and
  • ![ - main.306)<a href="https://scholar.google.com.hk/scholar?q=OpenIE6:+Iterative+Grid+Labeling+and+Coordination+Analysis+for+Open+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**OpenIE6: Iterative Grid Labeling and Coordination Analysis for Open Information Extraction**](https://www.aclweb.org/anthology/2020.emnlp-main.306) , <br> by *Kolluru, Keshav and
  • ![ - main.304)<a href="https://scholar.google.com.hk/scholar?q=Recurrent+Interaction+Network+for+Jointly+Extracting+Entities+and+Classifying+Relations"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Recurrent Interaction Network for Jointly Extracting Entities and Classifying Relations**](https://www.aclweb.org/anthology/2020.emnlp-main.304) , <br> by *Sun, Kai and
  • ![ - main.302)<a href="https://scholar.google.com.hk/scholar?q=Exposing+Shallow+Heuristics+of+Relation+Extraction+Models+with+Challenge+Data"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Exposing Shallow Heuristics of Relation Extraction Models with Challenge Data**](https://www.aclweb.org/anthology/2020.emnlp-main.302) , <br> by *Rosenman, Shachar and
  • ![ - main.301)<a href="https://scholar.google.com.hk/scholar?q=Let's+Stop+Incorrect+Comparisons+in+End-to-end+Relation+Extraction!"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Let's Stop Incorrect Comparisons in End-to-end Relation Extraction!**](https://www.aclweb.org/anthology/2020.emnlp-main.301) , <br> by *Taill{\'e}, Bruno and
  • ![ - main.300)<a href="https://scholar.google.com.hk/scholar?q=Denoising+Relation+Extraction+from+Document-level+Distant+Supervision"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Denoising Relation Extraction from Document-level Distant Supervision**](https://www.aclweb.org/anthology/2020.emnlp-main.300) , <br> by *Xiao, Chaojun and
  • ![ - main.299)<a href="https://scholar.google.com.hk/scholar?q=SelfORE:+Self-supervised+Relational+Feature+Learning+for+Open+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**SelfORE: Self-supervised Relational Feature Learning for Open Relation Extraction**](https://www.aclweb.org/anthology/2020.emnlp-main.299) , <br> by *Hu, Xuming and
  • ![ - main.298)<a href="https://scholar.google.com.hk/scholar?q=Learning+from+Context+or+Names?+An+Empirical+Study+on+Neural+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Learning from Context or Names? An Empirical Study on Neural Relation Extraction**](https://www.aclweb.org/anthology/2020.emnlp-main.298) , <br> by *Peng, Hao and
  • ![ - main.153)<a href="https://scholar.google.com.hk/scholar?q=An+Information+Bottleneck+Approach+for+Controlling+Conciseness+in+Rationale+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**An Information Bottleneck Approach for Controlling Conciseness in Rationale Extraction**](https://www.aclweb.org/anthology/2020.emnlp-main.153) , <br> by *Paranjape, Bhargavi and
  • ![ - main.132)<a href="https://scholar.google.com.hk/scholar?q=Pre-training+Entity+Relation+Encoder+with+Intra-span+and+Inter-span+Information"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Pre-training Entity Relation Encoder with Intra-span and Inter-span Information**](https://www.aclweb.org/anthology/2020.emnlp-main.132) , <br> by *Wang, Yijun and
  • ![ - main.133)<a href="https://scholar.google.com.hk/scholar?q=Two+are+Better+than+One:+Joint+Entity+and+Relation+Extraction+with+Table-Sequence+Encoders"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders**](https://www.aclweb.org/anthology/2020.emnlp-main.133) , <br> by *Wang, Jue and
  • ![ - main.128)<a href="https://scholar.google.com.hk/scholar?q=Event+Extraction+as+Machine+Reading+Comprehension"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Event Extraction as Machine Reading Comprehension**](https://www.aclweb.org/anthology/2020.emnlp-main.128) , <br> by *Liu, Jian and
  • ![ - main.51)<a href="https://scholar.google.com.hk/scholar?q=Joint+Constrained+Learning+for+Event-Event+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Joint Constrained Learning for Event-Event Relation Extraction**](https://www.aclweb.org/anthology/2020.emnlp-main.51) , <br> by *Wang, Haoyu and
  • ![ - main.49)<a href="https://scholar.google.com.hk/scholar?q=Event+Extraction+by+Answering+(Almost)+Natural+Questions"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Event Extraction by Answering (Almost) Natural Questions**](https://www.aclweb.org/anthology/2020.emnlp-main.49) , <br> by *Du, Xinya and
  • ![ - main.582)<a href="https://scholar.google.com.hk/scholar?q=Coreferential+Reasoning+Learning+for+Language+Representation"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Coreferential Reasoning Learning for Language Representation**](https://doi.org/10.18653/v1/2020.emnlp-main.582) , <br> by *Deming Ye and
  • ![ - main.127)<a href="https://scholar.google.com.hk/scholar?q=Double+Graph+Based+Reasoning+for+Document-level+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Double Graph Based Reasoning for Document-level Relation Extraction**](https://doi.org/10.18653/v1/2020.emnlp-main.127) , <br> by *Shuang Zeng and
  • ![ - main.303)<a href="https://scholar.google.com.hk/scholar?q=Global-to-Local+Neural+Networks+for+Document-Level+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Global-to-Local Neural Networks for Document-Level Relation Extraction**](https://doi.org/10.18653/v1/2020.emnlp-main.303) , <br> by *Difeng Wang and
  • ![ - 1649)<a href="https://scholar.google.com.hk/scholar?q=FewRel+2.0:+Towards+More+Challenging+Few-Shot+Relation+Classification"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**FewRel 2.0: Towards More Challenging Few-Shot Relation Classification**](https://doi.org/10.18653/v1/D19-1649) , <br> by *Tianyu Gao and
  • ![ - 1498)<a href="https://scholar.google.com.hk/scholar?q=Connecting+the+Dots:+Document-level+Neural+Relation+Extraction+with+Edge-oriented+Graphs"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Connecting the Dots: Document-level Neural Relation Extraction with
  • ![ - 1514)<a href="https://scholar.google.com.hk/scholar?q=FewRel:+A+Large-Scale+Supervised+Few-shot+Relation+Classification+Dataset+with+State-of-the-Art+Evaluation"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**FewRel: A Large-Scale Supervised Few-shot Relation Classification
  • ![ - 1200)<a href="https://scholar.google.com.hk/scholar?q=Modeling+Joint+Entity+and+Relation+Extraction+with+Table+Representation"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Modeling Joint Entity and Relation Extraction with Table Representation**](https://doi.org/10.3115/v1/d14-1200) , <br> by *Makoto Miwa and
  • ![ - 1010/)<a href="https://scholar.google.com.hk/scholar?q=Kernel+Methods+for+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Kernel Methods for Relation Extraction**](https://aclanthology.org/W02-1010/) , <br> by *Dmitry Zelenko and
  • ![ - main.370)<a href="https://scholar.google.com.hk/scholar?q=A+Two-Stream+AMR-enhanced+Model+for+Document-level+Event+Argument+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction**](https://aclanthology.org/2022.naacl-main.370) , <br> by *Xu, Runxin and
  • ![ - main.65)<a href="https://scholar.google.com.hk/scholar?q=CompactIE:+Compact+Facts+in+Open+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**CompactIE: Compact Facts in Open Information Extraction**](https://aclanthology.org/2022.naacl-main.65) , <br> by *Fatahi Bayat, Farima and
  • ![ - main.375)<a href="https://scholar.google.com.hk/scholar?q=Modeling+Multi-Granularity+Hierarchical+Features+for+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Modeling Multi-Granularity Hierarchical Features for Relation Extraction**](https://aclanthology.org/2022.naacl-main.375) , <br> by *Liang, Xinnian and
  • ![ - main.282)<a href="https://scholar.google.com.hk/scholar?q=Does+it+Really+Generalize+Well+on+Unseen+Data?+Systematic+Evaluation+of+Relational+Triple+Extraction+Methods"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Does it Really Generalize Well on Unseen Data? Systematic Evaluation of Relational Triple Extraction Methods**](https://aclanthology.org/2022.naacl-main.282) , <br> by *Lee, Juhyuk and
  • ![ - main.395)<a href="https://scholar.google.com.hk/scholar?q=Modeling+Task+Interactions+in+Document-Level+Joint+Entity+and+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Modeling Task Interactions in Document-Level Joint Entity and Relation Extraction**](https://aclanthology.org/2022.naacl-main.395) , <br> by *Xu, Liyan and
  • ![ - main.291)<a href="https://scholar.google.com.hk/scholar?q=DocEE:+A+Large-Scale+and+Fine-grained+Benchmark+for+Document-level+Event+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**DocEE: A Large-Scale and Fine-grained Benchmark for Document-level Event Extraction**](https://aclanthology.org/2022.naacl-main.291) , <br> by *Tong, MeiHan and
  • ![ - main.421)<a href="https://scholar.google.com.hk/scholar?q=Few-Shot+Document-Level+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Few-Shot Document-Level Relation Extraction**](https://aclanthology.org/2022.naacl-main.421) , <br> by *Popovic, Nicholas and
  • ![ - main.109)<a href="https://scholar.google.com.hk/scholar?q=Relation-Specific+Attentions+over+Entity+Mentions+for+Enhanced+Document-Level+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Relation-Specific Attentions over Entity Mentions for Enhanced Document-Level Relation Extraction**](https://aclanthology.org/2022.naacl-main.109) , <br> by *Yu, Jiaxin and
  • ![ - main.212)<a href="https://scholar.google.com.hk/scholar?q=Document-Level+Relation+Extraction+with+Sentences+Importance+Estimation+and+Focusing"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Document-Level Relation Extraction with Sentences Importance Estimation and Focusing**](https://aclanthology.org/2022.naacl-main.212) , <br> by *Xu, Wang and
  • ![ - main.324)<a href="https://scholar.google.com.hk/scholar?q=Joint+Extraction+of+Entities,+Relations,+and+Events+via+Modeling+Inter-Instance+and+Inter-Label+Dependencies"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Joint Extraction of Entities, Relations, and Events via Modeling Inter-Instance and Inter-Label Dependencies**](https://aclanthology.org/2022.naacl-main.324) , <br> by *Nguyen, Minh Van and
  • ![ - main.437)<a href="https://scholar.google.com.hk/scholar?q=HiURE:+Hierarchical+Exemplar+Contrastive+Learning+for+Unsupervised+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**HiURE: Hierarchical Exemplar Contrastive Learning for Unsupervised Relation Extraction**](https://aclanthology.org/2022.naacl-main.437) , <br> by *Liu, Shuliang and
  • ![ - main.222)<a href="https://scholar.google.com.hk/scholar?q=Document-Level+Event+Argument+Extraction+by+Leveraging+Redundant+Information+and+Closed+Boundary+Loss"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Document-Level Event Argument Extraction by Leveraging Redundant Information and Closed Boundary Loss**](https://aclanthology.org/2022.naacl-main.222) , <br> by *Zhou, Hanzhang and
  • ![ - main.224)<a href="https://scholar.google.com.hk/scholar?q=Should+We+Rely+on+Entity+Mentions+for+Relation+Extraction?+Debiasing+Relation+Extraction+with+Counterfactual+Analysis"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis**](https://aclanthology.org/2022.naacl-main.224) , <br> by *Wang, Yiwei and
  • ![ - main.48)<a href="https://scholar.google.com.hk/scholar?q=EmRel:+Joint+Representation+of+Entities+and+Embedded+Relations+for+Multi-triple+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple Extraction**](https://aclanthology.org/2022.naacl-main.48) , <br> by *Xu, Benfeng and
  • ![ - main.138)<a href="https://scholar.google.com.hk/scholar?q=DEGREE:+A+Data-Efficient+Generation-Based+Event+Extraction+Model"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**DEGREE: A Data-Efficient Generation-Based Event Extraction Model**](https://aclanthology.org/2022.naacl-main.138) , <br> by *Hsu, I-Hung and
  • ![ - main.342)<a href="https://scholar.google.com.hk/scholar?q=GenIE:+Generative+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**GenIE: Generative Information Extraction**](https://aclanthology.org/2022.naacl-main.342) , <br> by *Josifoski, Martin and
  • ![ - main.160)<a href="https://scholar.google.com.hk/scholar?q=Generic+and+Trend-aware+Curriculum+Learning+for+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Generic and Trend-aware Curriculum Learning for Relation Extraction**](https://aclanthology.org/2022.naacl-main.160) , <br> by *Vakil, Nidhi and
  • ![ - main.367)<a href="https://scholar.google.com.hk/scholar?q=RAAT:+Relation-Augmented+Attention+Transformer+for+Relation+Modeling+in+Document-Level+Event+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**RAAT: Relation-Augmented Attention Transformer for Relation Modeling in Document-Level Event Extraction**](https://aclanthology.org/2022.naacl-main.367) , <br> by *Liang, Yuan and
  • ![ - main.171)<a href="https://scholar.google.com.hk/scholar?q=SAIS:+Supervising+and+Augmenting+Intermediate+Steps+for+Document-Level+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction**](https://aclanthology.org/2022.naacl-main.171) , <br> by *Xiao, Yuxin and
  • ![ - main.276)<a href="https://scholar.google.com.hk/scholar?q=GMN:+Generative+Multi-modal+Network+for+Practical+Document+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**GMN: Generative Multi-modal Network for Practical Document Information Extraction**](https://aclanthology.org/2022.naacl-main.276) , <br> by *Cao, Haoyu and
  • ![ - main.2)<a href="https://scholar.google.com.hk/scholar?q=Distantly+Supervised+Relation+Extraction+with+Sentence+Reconstruction+and+Knowledge+Base+Priors"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Distantly Supervised Relation Extraction with Sentence Reconstruction and Knowledge Base Priors**](https://www.aclweb.org/anthology/2021.naacl-main.2) , <br> by *Christopoulou, Fenia and
  • ![ - main.5)<a href="https://scholar.google.com.hk/scholar?q=A+Frustratingly+Easy+Approach+for+Entity+and+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**A Frustratingly Easy Approach for Entity and Relation Extraction**](https://www.aclweb.org/anthology/2021.naacl-main.5) , <br> by *Zhong, Zexuan and
  • ![ - main.272)<a href="https://scholar.google.com.hk/scholar?q=ZS-BERT:+Towards+Zero-Shot+Relation+Extraction+with+Attribute+Representation+Learning"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**ZS-BERT: Towards Zero-Shot Relation Extraction with Attribute Representation Learning**](https://www.aclweb.org/anthology/2021.naacl-main.272) , <br> by *Chen, Chih-Yao and
  • ![ - main.453)<a href="https://scholar.google.com.hk/scholar?q=Jointly+Extracting+Explicit+and+Implicit+Relational+Triples+with+Reasoning+Pattern+Enhanced+Binary+Pointer+Network"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Jointly Extracting Explicit and Implicit Relational Triples with Reasoning Pattern Enhanced Binary Pointer Network**](https://www.aclweb.org/anthology/2021.naacl-main.453) , <br> by *Chen, Yubo and
  • ![ - main.3)<a href="https://scholar.google.com.hk/scholar?q=Cross-Task+Instance+Representation+Interactions+and+Label+Dependencies+for+Joint+Information+Extraction+with+Graph+Convolutional+Networks"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks**](https://www.aclweb.org/anthology/2021.naacl-main.3) , <br> by *Nguyen, Minh Van and
  • ![ - main.4)<a href="https://scholar.google.com.hk/scholar?q=Abstract+Meaning+Representation+Guided+Graph+Encoding+and+Decoding+for+Joint+Information+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Abstract Meaning Representation Guided Graph Encoding and Decoding for Joint Information Extraction**](https://www.aclweb.org/anthology/2021.naacl-main.4) , <br> by *Zhang, Zixuan and
  • ![ - main.452)<a href="https://scholar.google.com.hk/scholar?q=Open+Hierarchical+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Open Hierarchical Relation Extraction**](https://www.aclweb.org/anthology/2021.naacl-main.452) , <br> by *Zhang, Kai and
  • ![ - main.69/)<a href="https://scholar.google.com.hk/scholar?q=Document-Level+Event+Argument+Extraction+by+Conditional+Generation"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Document-Level Event Argument Extraction by Conditional Generation**](https://www.aclweb.org/anthology/2021.naacl-main.69/) , <br> by *Sha Li and
  • ![ - 2401)<a href="https://scholar.google.com.hk/scholar?q=A+Linear+Programming+Formulation+for+Global+Inference+in+Natural+Language+Tasks"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**A Linear Programming Formulation for Global Inference in Natural Language Tasks**](https://aclanthology.org/W04-2401) , <br> by *Roth, Dan and
  • ![ - main.138)<a href="https://scholar.google.com.hk/scholar?q=TPLinker:+Single-stage+Joint+Extraction+of+Entities+and+Relations+Through+Token+Pair+Linking"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**TPLinker: Single-stage Joint Extraction of Entities and Relations Through Token Pair Linking**](https://doi.org/10.18653/v1/2020.coling-main.138) , <br> by *Yucheng Wang and
  • ![ - main.563)<a href="https://scholar.google.com.hk/scholar?q=Bridging+Text+and+Knowledge+with+Multi-Prototype+Embedding+for+Few-Shot+Relational+Triple+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Bridging Text and Knowledge with Multi-Prototype Embedding for Few-Shot
  • ![ - main.461)<a href="https://scholar.google.com.hk/scholar?q=Global+Context-enhanced+Graph+Convolutional+Networks+for+Document-level+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Global Context-enhanced Graph Convolutional Networks for Document-level
  • ![ - main.143)<a href="https://scholar.google.com.hk/scholar?q=Document-level+Relation+Extraction+with+Dual-tier+Heterogeneous+Graph"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Document-level Relation Extraction with Dual-tier Heterogeneous Graph**](https://doi.org/10.18653/v1/2020.coling-main.143) , <br> by *Zhenyu Zhang and
  • ![ - main.136)<a href="https://scholar.google.com.hk/scholar?q=Graph+Enhanced+Dual+Attention+Network+for+Document-Level+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Graph Enhanced Dual Attention Network for Document-Level Relation
  • ![ - 1239/)<a href="https://scholar.google.com.hk/scholar?q=Table+Filling+Multi-Task+Recurrent+Neural+Network+for+Joint+Entity+and+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Table Filling Multi-Task Recurrent Neural Network for Joint Entity
  • ![ - main.166)<a href="https://scholar.google.com.hk/scholar?q=Multilingual+Entity+and+Relation+Extraction+Dataset+and+Model"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Multilingual Entity and Relation Extraction Dataset and Model**](https://www.aclweb.org/anthology/2021.eacl-main.166) , <br> by *Seganti, Alessandro and
  • ![ - main.172)<a href="https://scholar.google.com.hk/scholar?q=Learning+Relatedness+between+Types+with+Prototypes+for+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Learning Relatedness between Types with Prototypes for Relation Extraction**](https://www.aclweb.org/anthology/2021.eacl-main.172) , <br> by *Fu, Lisheng and
  • ![ - main.251)<a href="https://scholar.google.com.hk/scholar?q=ENPAR:Enhancing+Entity+and+Entity+Pair+Representations+for+Joint+Entity+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**ENPAR:Enhancing Entity and Entity Pair Representations for Joint Entity Relation Extraction**](https://www.aclweb.org/anthology/2021.eacl-main.251) , <br> by *Wang, Yijun and
  • ![ - main.290)<a href="https://scholar.google.com.hk/scholar?q=Modeling+Coreference+Relations+in+Visual+Dialog"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Modeling Coreference Relations in Visual Dialog**](https://www.aclweb.org/anthology/2021.eacl-main.290) , <br> by *Li, Mingxiao and
  • ![ - main.319)<a href="https://scholar.google.com.hk/scholar?q=An+End-to-end+Model+for+Entity-level+Relation+Extraction+using+Multi-instance+Learning"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**An End-to-end Model for Entity-level Relation Extraction using Multi-instance Learning**](https://www.aclweb.org/anthology/2021.eacl-main.319) , <br> by *Eberts, Markus and
  • ![ - main.321)<a href="https://scholar.google.com.hk/scholar?q=Two+Training+Strategies+for+Improving+Relation+Extraction+over+Universal+Graph"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Two Training Strategies for Improving Relation Extraction over Universal Graph**](https://www.aclweb.org/anthology/2021.eacl-main.321) , <br> by *Dai, Qin and
  • ![ - main.319/)<a href="https://scholar.google.com.hk/scholar?q=An+End-to-end+Model+for+Entity-level+Relation+Extraction+using+Multi-instance+Learning"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**An End-to-end Model for Entity-level Relation Extraction using Multi-instance
  • ![ - main.52/)<a href="https://scholar.google.com.hk/scholar?q=GRIT:+Generative+Role-filler+Transformers+for+Document-level+Event+Entity+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**GRIT: Generative Role-filler Transformers for Document-level Event
  • ![ - main.128/)<a href="https://scholar.google.com.hk/scholar?q=Bootstrapping+Relation+Extractors+using+Syntactic+Search+by+Examples"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Bootstrapping Relation Extractors using Syntactic Search by Examples**](https://www.aclweb.org/anthology/2021.eacl-main.128/) , <br> by *Matan Eyal and
  • ![ - main.75/)<a href="https://scholar.google.com.hk/scholar?q=More+Data,+More+Relations,+More+Context+and+More+Openness:+A+Review+and+Outlook+for+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**More Data, More Relations, More Context and More Openness: A Review
  • ![ - shot+Relation+Extraction+via+Bayesian+Meta-learning+on+Relation+Graphs"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs**](http://proceedings.mlr.press/v119/qu20a.html) , <br> by *Qu, Meng, Gao, Tianyu, Xhonneux, Louis-Pascal and Tang, Jian* [[bib]](https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/./bibtex.bib#L2605-L2612) </details><details><summary><img src=https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/scripts/svg/copy_icon.png height="20" align="bottom"></summary><pre>```pmlr-v119-qu20a```
  • ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Prototypical Representation Learning for Relation Extraction**](https://openreview.net/forum?id=aCgLmfhIy\_f) , <br> by *Ning Ding and
  • ![ - Abstract.html)<a href="https://scholar.google.com.hk/scholar?q=Knowledge+Extraction+with+No+Observable+Data"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Knowledge Extraction with No Observable Data**](https://proceedings.neurips.cc/paper/2019/hash/596f713f9a7376fe90a62abaaedecc2d-Abstract.html) , <br> by *Jaemin Yoo and
  • ![ - 3-642-15939-8\_10)<a href="https://scholar.google.com.hk/scholar?q=Modeling+Relations+and+Their+Mentions+without+Labeled+Text"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Modeling Relations and Their Mentions without Labeled Text**](https://doi.org/10.1007/978-3-642-15939-8\_10) , <br> by *Sebastian Riedel and
  • ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Multimodal Relation Extraction with Efficient Graph Alignment**](https://doi.org/10.1145/3474085.3476968) , <br> by *Changmeng Zheng and
  • ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Multimodal Relation Extraction with Efficient Graph Alignment**](https://doi.org/10.1145/3474085.3476968) , <br> by *Changmeng Zheng and
  • ![ - Shot+Event+Detection"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Graph Learning Regularization and Transfer Learning for Few-Shot Event Detection**](https://doi.org/10.1145/3404835.3463054) , <br> by *Lai, Viet Dac, Nguyen, Minh Van, Nguyen, Thien Huu and Dernoncourt, Franck* [[bib]](https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/./bibtex.bib#L1342-L1349) </details><details><summary><img src=https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/scripts/svg/copy_icon.png height="20" align="bottom"></summary><pre>```3404835.3463054```
  • ![ - Enhanced+Domain+Adaptation+in+Few-Shot+Relation+Classification"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Knowledge-Enhanced Domain Adaptation in Few-Shot Relation Classification**](https://doi.org/10.1145/3447548.3467438) , <br> by *Zhang, Jiawen, Zhu, Jiaqi, Yang, Yi, Shi, Wandong, Zhang, Congcong and Wang, Hongan* [[bib]](https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/./bibtex.bib#L1287-L1294) </details><details><summary><img src=https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/scripts/svg/copy_icon.png height="20" align="bottom"></summary><pre>```3447548.3467438```
  • ![ - TACRED:+Addressing+Shortcomings+of+the+TACRED+Dataset"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Re-TACRED: Addressing Shortcomings of the TACRED Dataset**](https://ojs.aaai.org/index.php/AAAI/article/view/17631) , <br> by *George Stoica and
  • ![ - MSRE:+A+Few-Shot+Learning+based+Approach+to+Multimodal+Social+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**FL-MSRE: A Few-Shot Learning based Approach to Multimodal Social
  • ![ - Meta+Learning+for+Order-Robust+Continual+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Curriculum-Meta Learning for Order-Robust Continual Relation Extraction**](https://ojs.aaai.org/index.php/AAAI/article/view/17241) , <br> by *Tongtong Wu and
  • ![ - Level+Relation+Extraction+with+Adaptive+Thresholding+and+Localized+Context+Pooling"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Document-Level Relation Extraction with Adaptive Thresholding and
  • ![ - Level+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Entity Structure Within and Throughout: Modeling Mention Dependencies
  • ![ - view+Inference+for+Relation+Extraction+with+Uncertain+Knowledge"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Multi-view Inference for Relation Extraction with Uncertain Knowledge**](https://ojs.aaai.org/index.php/AAAI/article/view/17563) , <br> by *Bo Li and
  • ![ - Level+Relation+Extraction+with+Reconstruction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Document-Level Relation Extraction with Reconstruction**](https://ojs.aaai.org/index.php/AAAI/article/view/17667) , <br> by *Wang Xu and
  • ![ - Shot+Relation+Learning"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Neural Snowball for Few-Shot Relation Learning**](https://aaai.org/ojs/index.php/AAAI/article/view/6281) , <br> by *Tianyu Gao and
  • ![ - Based+Prototypical+Networks+for+Noisy+Few-Shot+Relation+Classification"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation
  • ![ - level+Relation+Extraction+as+Semantic+Segmentation"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Document-level Relation Extraction as Semantic Segmentation**](https://doi.org/10.24963/ijcai.2021/551) , <br> by *Zhang, Ningyu, Chen, Xiang, Xie, Xin, Deng, Shumin, Tan, Chuanqi, Chen, Mosha, Huang, Fei, Si, Luo and Chen, Huajun* [[bib]](https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/./bibtex.bib#L1055-L1062) </details><details><summary><img src=https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/scripts/svg/copy_icon.png height="20" align="bottom"></summary><pre>```ijcai2021-551```
  • ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Consistent Inference for Dialogue Relation Extraction**](https://doi.org/10.24963/ijcai.2021/535) , <br> by *Long, Xinwei, Niu, Shuzi and Li, Yucheng* [[bib]](https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/./bibtex.bib#L1067-L1074) </details><details><summary><img src=https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/scripts/svg/copy_icon.png height="20" align="bottom"></summary><pre>```ijcai2021-535```
  • ![ - Based+Joint+Entity+and+Relation+Extraction+with+Transformer+Pre-Training"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Span-Based Joint Entity and Relation Extraction with Transformer Pre-Training**](https://doi.org/10.3233/FAIA200321) , <br> by *Markus Eberts and
  • ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**CoType: Joint Extraction of Typed Entities and Relations with Knowledge
  • ![ - 1.42)<a href="https://scholar.google.com.hk/scholar?q=Revisiting+Few-shot+Relation+Classification:+Evaluation+Data+and+Classification+Schemes"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Revisiting Few-shot Relation Classification: Evaluation Data and Classification Schemes**](https://aclanthology.org/2021.tacl-1.42) , <br> by *Sabo, Ofer and
  • ![ - A+Large-Scale+Document-Level+RelatSentence+N-ary+Relation+Extraction+with+Graph+LSTMs"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Cross-A Large-Scale Document-Level RelatSentence N-ary Relation Extraction with Graph LSTMs**](https://transacl.org/ojs/index.php/tacl/article/view/1028) , <br> by *Nanyun Peng and
  • ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Relation Extraction Using Distant Supervision: A Survey**](https://doi.org/10.1145/3241741) , <br> by *Alisa Smirnova and
  • ![ - 1.4)<a href="https://scholar.google.com.hk/scholar?q=Document-level+Event+Extraction+with+Efficient+End-to-end+Learning+of+Cross-event+Dependencies"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Document-level Event Extraction with Efficient End-to-end Learning of Cross-event Dependencies**](https://www.aclweb.org/anthology/2021.nuse-1.4) , <br> by *Huang, Kung-Hsiang and
  • ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Good Visual Guidance Makes A Better Extractor: Hierarchical Visual Prefix for Multimodal Entity and Relation Extraction**](https://arxiv.org/abs/2205.03521) , <br> by *Chen, Xiang, Zhang, Ningyu, Li, Lei, Yao, Yunzhi, Deng, Shumin, Tan, Chuanqi, Huang, Fei, Si, Luo and Chen, Huajun* [[bib]](https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/./bibtex.bib#L2799-L2812) </details><details><summary><img src=https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/scripts/svg/copy_icon.png height="20" align="bottom"></summary><pre>```2205.03521```
  • ![ - based+Finetuning+for+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**AdaPrompt: Adaptive Prompt-based Finetuning for Relation Extraction**](https://arxiv.org/abs/2104.07650) , <br> by *Xiang Chen and
  • ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Event Extraction as Natural Language Generation**](https://arxiv.org/abs/2108.12724) , <br> by *I-Hung Hsu, Kuan-Hao Huang, Elizabeth Boschee, Scott Miller, Prem Natarajan, Kai-Wei Chang and Nanyun Peng* [[bib]](https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/./bibtex.bib#L2687-L2694) </details><details><summary><img src=https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/scripts/svg/copy_icon.png height="20" align="bottom"></summary><pre>```hsu2021event```
  • ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**ESTER: A Machine Reading Comprehension Dataset for Event Semantic
  • ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Knowing False Negatives: An Adversarial Training Method for Distantly Supervised Relation Extraction**](https://arxiv.org/abs/2109.02099) , <br> by *Kailong Hao, Botao Yu and Wei Hu* [[bib]](https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/./bibtex.bib#L2717-L2724) </details><details><summary><img src=https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/scripts/svg/copy_icon.png height="20" align="bottom"></summary><pre>```hao2021knowing```
  • ![ - based+Open-Domain+Event+Type+Induction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Corpus-based Open-Domain Event Type Induction**](https://arxiv.org/abs/2109.03322) , <br> by *Jiaming Shen, Yunyi Zhang, Heng Ji and Jiawei Han* [[bib]](https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/./bibtex.bib#L2727-L2734) ```EMNLP 2021. Proposing a new method for open event extraction.
  • ![ - Oriented+Latent+Structures+for+Dialogue-Based+Relation+Extraction"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Speaker-Oriented Latent Structures for Dialogue-Based Relation Extraction**](https://arxiv.org/abs/2109.05182) , <br> by *Guoshun Nan, Guoqing Luo, Sicong Leng, Yao Xiao and Wei Lu* [[bib]](https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/./bibtex.bib#L2737-L2744) ```EMNLP 2021
  • ![ - Learning+for+Fine-Grained+Entity+Typing"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Prompt-Learning for Fine-Grained Entity Typing**](https://arxiv.org/abs/2108.10604) , <br> by *Ning Ding and
  • ![ - guided+Attention+for+Low-resource+NER"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**LightNER: A Lightweight Generative Framework with Prompt-guided Attention for Low-resource NER**](https://arxiv.org/abs/2109.00720) , <br> by *Xiang Chen, Ningyu Zhang, Lei Li, Xin Xie, Shumin Deng, Chuanqi Tan, Fei Huang, Luo Si and Huajun Chen* [[bib]](https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/./bibtex.bib#L2764-L2771) </details><details><summary><img src=https://github.com/wutong8023/Awesome_Information_Extraction/blob/master/scripts/svg/copy_icon.png height="20" align="bottom"></summary><pre>```chen2021lightner```
  • ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**DRILL: Dynamic Representations for Imbalanced Lifelong Learning**](https://arxiv.org/abs/2105.08445) , <br> by *Kyra Ahrens and
  • ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Entity and Evidence Guided Relation Extraction for DocRED**](https://arxiv.org/abs/2008.12283) , <br> by *Kevin Huang and
  • ![ - supervised+Relation+Extraction+via+Incremental+Meta+Self-Training"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Semi-supervised Relation Extraction via Incremental Meta Self-Training**](https://arxiv.org/abs/2010.16410) , <br> by *Xuming Hu and
  • ![ - tune+Bert+for+DocRED+with+Two-step+Process"><img src="https://img.shields.io/badge/-blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"></a> [**Fine-tune Bert for DocRED with Two-step Process**](http://arxiv.org/abs/1909.11898) , <br> by *Hong Wang and