NLPExplorer

COLING - 2020

Total Papers:- 1363

Total Papers accross all years:- 7736

Total Citations :- 0

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YNU-oxz at SemEval-2020 Task 5: Detecting Counterfactuals Based on Ordered Neurons LSTM and Hierarchical Attention Network

Xiaozhi Ou | Shengyan Liu | Hongling Li |

Go Simple and Pre-Train on Domain-Specific Corpora: On the Role of Training Data for Text Classification

Aleksandra Edwards | Jose Camacho-Collados | Hélène De Ribaupierre | Alun Preece |

PG-GSQL: Pointer-Generator Network with Guide Decoding for Cross-Domain Context-Dependent Text-to-SQL Generation

Huajie Wang | Mei Li | Lei Chen |

Delexicalized Paraphrase Generation

Boya Yu | Konstantine Arkoudas | Wael Hamza |

DiaSense at SemEval-2020 Task 1: Modeling Sense Change via Pre-trained BERT Embeddings

Christin Beck |

Detecting Tweets Reporting Birth Defect Pregnancy Outcome Using Two-View CNN RNN Based Architecture

Saichethan Reddy |

Automatic Discovery of Heterogeneous Machine Learning Pipelines: An Application to Natural Language Processing

Suilan Estevez-Velarde | Yoan Gutiérrez | Andres Montoyo | Yudivián Almeida Cruz |

Sonal.kumari at SemEval-2020 Task 12: Social Media Multilingual Offensive Text Identification and Categorization Using Neural Network Models

Sonal Kumari |

NTUAAILS at SemEval-2020 Task 11: Propaganda Detection and Classification with biLSTMs and ELMo

Anastasios Arsenos | Georgios Siolas |

CN-HIT-IT.NLP at SemEval-2020 Task 4: Enhanced Language Representation with Multiple Knowledge Triples

FPAI at SemEval-2020 Task 10: A Query Enhanced Model with RoBERTa for Emphasis Selection

Proceedings of the 28th International Conference on Computational Linguistics: Tutorial Abstracts

Lucia Specia | Daniel Beck |

Pheonix at SemEval-2020 Task 5: Masking the Labels Lubricates Models for Sequence Labeling

Pouria Babvey | Dario Borrelli | Yutong Zhao | Carlo Lipizzi |

Leveraging Discourse Rewards for Document-Level Neural Machine Translation

Inigo Jauregi Unanue | Nazanin Esmaili | Gholamreza Haffari | Massimo Piccardi |