NLPExplorer

SemEval - 2022

Total Papers:- 234

Total Papers accross all years:- 1352

Total Citations :- 0

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Multilinguals at SemEval-2022 Task 11: Complex NER in Semantically Ambiguous Settings for Low Resource Languages

Amit Pandey | Swayatta Daw | Narendra Unnam | Vikram Pudi |

BL.Research at SemEval-2022 Task 1: Deep networks for Reverse Dictionary using embeddings and LSTM autoencoders

LISACTeam at SemEval-2022 Task 6: A Transformer based Approach for Intended Sarcasm Detection in English Tweets

Abdessamad Benlahbib | Hamza Alami | Ahmed Alami |

AIDA-UPM at SemEval-2022 Task 5: Exploring Multimodal Late Information Fusion for Multimedia Automatic Misogyny Identification

RubCSG at SemEval-2022 Task 5: Ensemble learning for identifying misogynous MEMEs

Wentao Yu | Benedikt Boenninghoff | Jonas Röhrig | Dorothea Kolossa |

niksss at SemEval-2022 Task 6: Are Traditionally Pre-Trained Contextual Embeddings Enough for Detecting Intended Sarcasm ?

Nikhil Singh |

IRB-NLP at SemEval-2022 Task 1: Exploring the Relationship Between Words and Their Semantic Representations

Damir Korenčić | Ivan Grubisic |

CSECU-DSG at SemEval-2022 Task 3: Investigating the Taxonomic Relationship Between Two Arguments using Fusion of Multilingual Transformer Models

Abdul Aziz | Md. Akram Hossain | Abu Nowshed Chy |

SemEval-2022 Task 4: Patronizing and Condescending Language Detection

Carla Perez-Almendros | Luis Espinosa-Anke | Steven Schockaert |

TeamOtter at SemEval-2022 Task 5: Detecting Misogynistic Content in Multimodal Memes

Paridhi Maheshwari | Sharmila Reddy Nangi |

GUTS at SemEval-2022 Task 4: Adversarial Training and Balancing Methods for Patronizing and Condescending Language Detection

JCT at SemEval-2022 Task 4-A: Patronism Detection in Posts Written in English using Preprocessing Methods and various Machine Leaerning Methods

Yaakov HaCohen-Kerner | Ilan Meyrowitsch | Matan Fchima |

BLCU-ICALL at SemEval-2022 Task 1: Cross-Attention Multitasking Framework for Definition Modeling

drsphelps at SemEval-2022 Task 2: Learning idiom representations using BERTRAM

Dylan Phelps |