Awesome_Information_Extraction
Literature Survey of Information Extraction, especially Relation Extraction, Event Extraction, and Slot Filling.
https://github.com/wutong8023/Awesome_Information_Extraction
Last synced: 11 days ago
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AAAI
- ![ - Level+Relation+Extraction+with+Reconstruction"> Document-Level Relation Extraction with Reconstruction , by *Wang Xu and
- ![ - Shot+Relation+Learning"> Neural Snowball for Few-Shot Relation Learning , by *Tianyu Gao and
- ![ - Based+Prototypical+Networks+for+Noisy+Few-Shot+Relation+Classification"> [**Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation
AACL
- ![ - main.75/) [**More Data, More Relations, More Context and More Openness: A Review
ACL
- ![ - short.38) PARE: A Simple and Strong Baseline for Monolingual and Multilingual Distantly Supervised Relation Extraction , by *Rathore, Vipul and
- ![ - acl.214) [**Adaptive Knowledge-Enhanced Bayesian Meta-Learning for Few-shot Event
- ![ - short.126) Three Sentences Are All You Need: Local Path Enhanced Document Relation Extraction , by *Huang, Quzhe and
- ![ - main.667) A Two-Step Approach for Implicit Event Argument Detection , by *Zhisong Zhang and
- ![ - 1074) DocRED: A Large-Scale Document-Level Relation Extraction Dataset , by *Yao, Yuan and
- ![ - 1047/) [**Extracting Relational Facts by an End-to-End Neural Model with Copy
- ![ - 1017) Creating Training Corpora for NLG Micro-Planners , by *Claire Gardent and
- ![ - 1038) Incremental Joint Extraction of Entity Mentions and Relations , by *Qi Li and
- ![ - 1056/) Exploiting Syntactico-Semantic Structures for Relation Extraction , by *Yee Seng Chan and
- ![ - 1053/) Exploring Various Knowledge in Relation Extraction , by *Guodong Zhou and
ACM Comput. Surv.
- ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"> Relation Extraction Using Distant Supervision: A Survey , by *Alisa Smirnova and
arXiv
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- blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"> Good Visual Guidance Makes A Better Extractor: Hierarchical Visual Prefix for Multimodal Entity and Relation Extraction , by Chen, Xiang, Zhang, Ningyu, Li, Lei, Yao, Yunzhi, Deng, Shumin, Tan, Chuanqi, Huang, Fei, Si, Luo and Chen, Huajun [bib]
2205.03521 - ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"> DRILL: Dynamic Representations for Imbalanced Lifelong Learning , by *Kyra Ahrens and
- ![ - supervised+Relation+Extraction+via+Incremental+Meta+Self-Training"> Semi-supervised Relation Extraction via Incremental Meta Self-Training , by *Xuming Hu and
- ![ - tune+Bert+for+DocRED+with+Two-step+Process"> Fine-tune Bert for DocRED with Two-step Process , by *Hong Wang and
COLING
EACL
- ![ - main.128/) Bootstrapping Relation Extractors using Syntactic Search by Examples , by *Matan Eyal and
ECAI
- ![ - Based+Joint+Entity+and+Relation+Extraction+with+Transformer+Pre-Training"> Span-Based Joint Entity and Relation Extraction with Transformer Pre-Training , by *Markus Eberts and
ECML
- ![ - 3-642-15939-8_10) Modeling Relations and Their Mentions without Labeled Text , by *Sebastian Riedel and
EMNLP
- ![ - main.271) Cost-effective End-to-end Information Extraction for Semi-structured Document Images , by *Hwang, Wonseok and
- ![ - main.303) Global-to-Local Neural Networks for Document-Level Relation Extraction , by *Difeng Wang and
- ![ - 1498) [**Connecting the Dots: Document-level Neural Relation Extraction with
- ![ - 1514) [**FewRel: A Large-Scale Supervised Few-shot Relation Classification
- ![ - 1200) Modeling Joint Entity and Relation Extraction with Table Representation , by *Makoto Miwa and
- ![ - 1010/) Kernel Methods for Relation Extraction , by *Dmitry Zelenko and
ICLR
- ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"> Prototypical Representation Learning for Relation Extraction , by *Ning Ding and
ICML
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- shot+Relation+Extraction+via+Bayesian+Meta-learning+on+Relation+Graphs"> 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
IJCAI
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- blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"> Consistent Inference for Dialogue Relation Extraction , by Long, Xinwei, Niu, Shuzi and Li, Yucheng [bib]
ijcai2021-535
KDD
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- Enhanced+Domain+Adaptation+in+Few-Shot+Relation+Classification"> 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
MM
- ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"> Multimodal Relation Extraction with Efficient Graph Alignment , by *Changmeng Zheng and
NAACL
- ![ - main.276) GMN: Generative Multi-modal Network for Practical Document Information Extraction , by *Cao, Haoyu and
- ![ - main.452) Open Hierarchical Relation Extraction , by *Zhang, Kai and
- ![ - main.69/) Document-Level Event Argument Extraction by Conditional Generation , by *Sha Li and
- ![ - 2401) A Linear Programming Formulation for Global Inference in Natural Language Tasks , by *Roth, Dan and
NeurIPS
- ![ - Abstract.html) Knowledge Extraction with No Observable Data , by *Jaemin Yoo and
NUSE-NAACL
- ![ - 1.4) Document-level Event Extraction with Efficient End-to-end Learning of Cross-event Dependencies , by *Huang, Kung-Hsiang and
Outline
SIGIR
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- Shot+Event+Detection"> 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
TACL
- ![ - 1.42) Revisiting Few-shot Relation Classification: Evaluation Data and Classification Schemes , by *Sabo, Ofer and
- ![ - A+Large-Scale+Document-Level+RelatSentence+N-ary+Relation+Extraction+with+Graph+LSTMs"> Cross-A Large-Scale Document-Level RelatSentence N-ary Relation Extraction with Graph LSTMs , by *Nanyun Peng and
WWW
- ![ - blue.svg?&logo=google-scholar&logoColor=white" height="18" align="bottom"> [**CoType: Joint Extraction of Typed Entities and Relations with Knowledge