- Phrase Mining
- Named Entity Recognition (NER)
- Relation Extraction (RE) and Open Information Extraction (OpenIE)
- Event Extraction
- Text Embedding
- Set Expansion and Synonym Discovery
- Taxonomy Expansion and Taxonomy Construction
- Text Classification
- Text Summarization and Question Answering
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(SIGMOD 2015) SegPhrase
Mining Quality Phrases from Massive Text Corpora [PDF] [Code] -
(IEEE TKDE 2018) AutoPhrase
Automated Phrase Mining from Massive Text Corpora [PDF] [Code] -
(KDD 2021) UCPhrase
UCPhrase: Unsupervised Context-aware Quality Phrase Tagging [PDF] [Code]
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(AAAI 2018) LM-LSTM-CRF
Empower Sequence Labeling with Task-Aware Neural Language Model [PDF] [Code] -
(EMNLP 2018) LD-Net
Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling [PDF] [Code] -
(EMNLP 2018) AutoNER
Learning Named Entity Tagger using Domain-Specific Dictionary [PDF] [Code] -
(Bioinformatics 2019) Multi-BioNER
Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning [PDF] [Code] -
(WANLP 2019) ArabicNER
Arabic Named Entity Recognition: What Works and What's Next [PDF] [Code] -
(EMNLP 2019) CrossWeigh
CrossWeigh: Training Named Entity Tagger from Imperfect Annotations [PDF] [Code] -
(EMNLP 2021) RoSTER
Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training [PDF] [Code] -
(Other models) VanillaNER and LightNER
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(KDD 2017) MetaPAD
MetaPAD: Meta Patten Discovery from Massive Text Corpora [PDF] [Code] -
(EMNLP 2017) ReHession
Heterogeneous Supervision for Relation Extraction: A Representation Learning Approach [PDF] [Code] -
(WSDM 2018) ReQuest
Indirect Supervision for Relation Extraction using Question-Answer Pairs [PDF] [Code] -
(WWW 2018) REPEL
Weakly-supervised Relation Extraction by Pattern-enhanced Embedding Learning [PDF] [Code] -
(WSDM 2019) ReMine
Integrating Local Context and Global Cohesiveness for Open Information Extraction [PDF] [Code]
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(NAACL-HLT 2021) Event Argument Extraction
Document-Level Event Argument Extraction by Conditional Generation [PDF] [Code] -
(EMNLP 2021) ETypeClus
Corpus-based Open-Domain Event Type Induction [PDF] [Code]
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(WWW 2020) CatE
Discriminative Topic Mining via Category-Name Guided Text Embedding [PDF] [Code] -
(KDD 2020) JoSH
Hierarchical Topic Mining via Joint Spherical Tree and Text Embedding [PDF] [Code]
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(ECML-PKDD 2017) SetExpan
SetExpan: Corpus-Based Set Expansion via Context Feature Selection and Rank Ensemble [PDF] [Code] -
(KDD 2017) DPE
Automatic Synonym Discovery with Knowledge Bases [PDF] [Code] -
(AAAI 2019) SynSetMine
Mining Entity Synonyms with Efficient Neural Set Generation [PDF] [Code] -
(ACL 2020) CGExpan
Empower Entity Set Expansion via Language Model Probing [PDF] [Code]
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(KDD 2018) TaxoGen
TaxoGen: Unsupervised Topic Taxonomy Construction by Adaptive Term Embedding and Clustering [PDF] [Code] -
(KDD 2018) HiExpan
HiExpan: Task-Guided Taxonomy Construction by Hierarchical Tree Expansion [PDF] [Code] -
(ACL 2018) TaxoRL
End-to-End Reinforcement Learning for Automatic Taxonomy Induction [PDF] [Code] -
(CIKM 2019) HyperMine
Discovering Hypernymy in Text-Rich Heterogeneous Information Network by Exploiting Context Granularity [PDF] [Code] -
(WWW 2020) TaxoExpan
TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network [PDF] [Code] -
(KDD 2020) CoRel
CoRel: Seed-Guided Topical Taxonomy Construction by Concept Learning and Relation Transferring [PDF] [Code]
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(CIKM 2018) WeSTClass
Weakly-Supervised Neural Text Classification [PDF] [Code] -
(AAAI 2019) WeSHClass
Weakly-Supervised Hierarchical Text Classification [PDF] [Code] -
(EMNLP 2019) HiLAP
Hierarchical Text Classification with Reinforced Label Assignment [PDF] [Code] -
(SIGIR 2020) MetaCat
Minimally Supervised Categorization of Text with Metadata [PDF] [Code] -
(EMNLP 2020) LOTClass
Text Classification Using Label Names Only: A Language Model Self-Training Approach [PDF] [Code] -
(EMNLP 2020) JASen
Weakly-Supervised Aspect-Based Sentiment Analysis via Joint Aspect-Sentiment Topic Embedding [PDF] [Code] -
(WSDM 2021) HIMECat
Hierarchical Metadata-Aware Document Categorization under Weak Supervision [PDF] [Code] -
(WWW 2021) MATCH
MATCH: Metadata-Aware Text Classification in A Large Hierarchy [PDF] [Code] -
(WWW 2021) LTRN
Minimally Supervised Structure Rich Text Categorization by Learning on Text-Rich Networks [PDF] [Code]
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(ACL 2020) FAR
Facet-Aware Evaluation for Extractive Summarization [PDF] [Code] -
(EMNLP 2020) RL-MMR
Multi-document Summarization with Maximal Marginal Relevance-guided Reinforcement Learning [PDF] [Code] -
(ACL 2021) GAR / RIDER
Generation-Augmented Retrieval for Open-domain Question Answering [PDF] [Code]
RIDER: Reader-Guided Passage Reranking for Open-Domain Question Answering [PDF] [Code] -
(EMNLP 2021) EDE
Extract, Denoise and Enforce: Evaluating and Improving Concept Preservation for Text-to-Text Generation [PDF] [Code]
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(CIKM 2017) MVE
An Attention-based Collaboration Framework for Multi-View Network Representation Learning [PDF] [Code] -
(SDM 2018) AspEm
AspEm: Embedding Learning by Aspects in Heterogeneous Information Networks [PDF] [Code] -
(KDD 2018) HEER
Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks [PDF] [Code] -
(ICDM 2018) HINSE
Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights [PDF] [Code] -
(AAAI 2019) DMGI
Unsupervised Attributed Multiplex Network Embedding [PDF] [Code] -
(TKDE 2020) HNE
Heterogeneous Network Representation Learning: A Unified Framework with Survey and Benchmark [PDF] [Code] -
(Other models) ESim
Meta-Path Guided Embedding for Similarity Search in Large-Scale Heterogeneous Information Networks [PDF] [Code]
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(WWW 2020) CG-MuAlign
Collective Multi-type Entity Alignment Between Knowledge Graphs [PDF] [Code] -
(IJCAI 2020) ALaGCN
AspEm: Embedding Learning by Aspects in Heterogeneous Information Networks [PDF] [Code] -
(NeurIPS 2021) EGI
Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization [PDF] [Code] -
(NeurIPS 2021) Shift-Robust GNNs
Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data [PDF] [Code]
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(ICLR 2020) RAdam
On the Variance of the Adaptive Learning Rate and Beyond [PDF] [Code] -
(EMNLP 2020) Admin
Understanding the Difficulty of Training Transformers [PDF] [Code] -
(Other models) TorchScope
See Illimine.
For more details on the team, please visit our official site here.