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SemEval 2022

233 papers

TUG-CIC at SemEval-2021 Task 6: Two-stage Fine-tuning for Intended Sarcasm Detection

Jason Angel, Segun Aroyehun, Alexander Gelbukh

connotation_clashers at SemEval-2022 Task 6: The effect of sentiment analysis on sarcasm detection

Patrick Hantsch, Nadav Chkroun

IISERB Brains at SemEval-2022 Task 6: A Deep-learning Framework to Identify Intended Sarcasm in English

Tanuj Shekhawat, Manoj Kumar, Udaybhan Rathore, Aditya Joshi, Jasabanta Patro

Plumeria at SemEval-2022 Task 6: Sarcasm Detection for English and Arabic Using Transformers and Data Augmentation

Mosab Shaheen, Shubham Kumar Nigam

ISD at SemEval-2022 Task 6: Sarcasm Detection Using Lightweight Models

Samantha Huang, Ethan Chi, Nathan Chi

Dartmouth at SemEval-2022 Task 6: Detection of Sarcasm

Rishik Lad, Weicheng Ma, Soroush Vosoughi

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

Nikhil Singh

reamtchka at SemEval-2022 Task 6: Investigating the effect of different loss functions for Sarcasm detection for unbalanced datasets

Reem Abdel-Salam

AlexU-AL at SemEval-2022 Task 6: Detecting Sarcasm in Arabic Text Using Deep Learning Techniques

Aya Lotfy, Marwan Torki, Nagwa El-Makky

akaBERT at SemEval-2022 Task 6: An Ensemble Transformer-based Model for Arabic Sarcasm Detection

Abdulrahman Mohamed Kamr, Ensaf Mohamed

BFCAI at SemEval-2022 Task 6: Multi-Layer Perceptron for Sarcasm Detection in Arabic Texts

Nsrin Ashraf, Fathy Elkazzaz, Mohamed Taha, Hamada Nayel, Tarek Elshishtawy

I2C at SemEval-2022 Task 6: Intended Sarcasm Detection on Social Networks with Deep Learning

Pablo Gonzalez Diaz, Pablo Cordon, Jacinto Mata, Victoria Pachón

UoR-NCL at SemEval-2022 Task 6: Using ensemble loss with BERT for intended sarcasm detection

Emmanuel Osei-Brefo, Huizhi Liang

NULL at SemEval-2022 Task 6: Intended Sarcasm Detection Using Stylistically Fused Contextualized Representation and Deep Learning

Mostafa Rahgouy, Hamed Babaei Giglou, Taher Rahgooy, Cheryl Seals

I2C at SemEval-2022 Task 6: Intended Sarcasm in English using Deep Learning Techniques

Adrián Moreno Monterde, Laura Vázquez Ramos, Jacinto Mata, Victoria Pachón Álvarez

TechSSN at SemEval-2022 Task 6: Intended Sarcasm Detection using Transformer Models

Rajalakshmi Sivanaiah, Angel Deborah S, Sakaya Milton R, Mirnalinee T T, Ramdhanush Venkatakrishnan

CS-UM6P at SemEval-2022 Task 6: Transformer-based Models for Intended Sarcasm Detection in English and Arabic

Abdelkader El Mahdaouy, Abdellah El Mekki, Kabil Essefar, Abderrahman Skiredj, Ismail Berrada

High Tech team at SemEval-2022 Task 6: Intended Sarcasm Detection for Arabic texts

Hamza Alami, Abdessamad Benlahbib, Ahmed Alami

Amrita_CEN at SemEval-2022 Task 6: A Machine Learning Approach for Detecting Intended Sarcasm using Oversampling

Aparna K Ajayan, Krishna Mohanan, Anugraha S, Premjith B, Soman Kp

GetSmartMSEC at SemEval-2022 Task 6: Sarcasm Detection using Contextual Word Embedding with Gaussian model for Irony Type Identification

Diksha Krishnan, Jerin Mahibha C, Thenmozhi Durairaj

stce at SemEval-2022 Task 6: Sarcasm Detection in English Tweets

Mengfei Yuan, Zhou Mengyuan, Lianxin Jiang, Yang Mo, Xiaofeng Shi

PALI-NLP at SemEval-2022 Task 6: iSarcasmEval- Fine-tuning the Pre-trained Model for Detecting Intended Sarcasm

Xiyang Du, Dou Hu, Jin Zhi, Lianxin Jiang, Xiaofeng Shi

SemEval-2022 Task 6: iSarcasmEval, Intended Sarcasm Detection in English and Arabic

Ibrahim Abu Farha, Silviu Vlad Oprea, Steven Wilson, Walid Magdy

Poirot at SemEval-2022 Task 5: Leveraging Graph Network for Misogynistic Meme Detection

Harshvardhan Srivastava

Exploring Contrastive Learning for Multimodal Detection of Misogynistic Memes

Charic Farinango Cuervo, Natalie Parde

YMAI at SemEval-2022 Task 5: Detecting Misogyny in Memes using VisualBERT and MMBT MultiModal Pre-trained Models

Mohammad Habash, Yahya Daqour, Malak Abdullah, Mahmoud Al-Ayyoub

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

Álvaro Huertas-García, Helena Liz, Guillermo Villar-Rodríguez, Alejandro Martín, Javier Huertas-Tato

R2D2 at SemEval-2022 Task 5: Attention is only as good as its Values! A multimodal system for identifying misogynist memes

Mayukh Sharma, Ilanthenral Kandasamy, Vasantha W B

TIB-VA at SemEval-2022 Task 5: A Multimodal Architecture for the Detection and Classification of Misogynous Memes

Sherzod Hakimov, Gullal Singh Cheema, Ralph Ewerth

YNU-HPCC at SemEval-2022 Task 5: Multi-Modal and Multi-label Emotion Classification Based on LXMERT

Chao Han, Jin Wang, Xuejie Zhang

UMUTeam at SemEval-2022 Task 5: Combining image and textual embeddings for multi-modal automatic misogyny identification

José García-Díaz, Camilo Caparros-Laiz, Rafael Valencia-García

QiNiAn at SemEval-2022 Task 5: Multi-Modal Misogyny Detection and Classification

Qin Gu, Nino Meisinger, Anna-Katharina Dick

IIT DHANBAD CODECHAMPS at SemEval-2022 Task 5: MAMI - Multimedia Automatic Misogyny Identification

Shubham Barnwal, Ritesh Kumar, Rajendra Pamula

IITR CodeBusters at SemEval-2022 Task 5: Misogyny Identification using Transformers

Gagan Sharma, Gajanan Sunil Gitte, Shlok Goyal, Raksha Sharma

Mitra Behzadi at SemEval-2022 Task 5 : Multimedia Automatic Misogyny Identification method based on CLIP

Mitra Behzadi, Ali Derakhshan, Ian Harris

University of Hildesheim at SemEval-2022 task 5: Combining Deep Text and Image Models for Multimedia Misogyny Detection

Milan Kalkenings, Thomas Mandl

AMS_ADRN at SemEval-2022 Task 5: A Suitable Image-text Multimodal Joint Modeling Method for Multi-task Misogyny Identification

Da Li, Ming Yi, Yukai He

MMVAE at SemEval-2022 Task 5: A Multi-modal Multi-task VAE on Misogynous Meme Detection

Yimeng Gu, Ignacio Castro, Gareth Tyson

INF-UFRGS at SemEval-2022 Task 5: analyzing the performance of multimodal models

Gustavo Lorentz, Viviane Moreira

I2C at SemEval-2022 Task 5: Identification of misogyny in internet memes

Pablo Cordon, Pablo Gonzalez Diaz, Jacinto Mata, Victoria Pachón

Codec at SemEval-2022 Task 5: Multi-Modal Multi-Transformer Misogynous Meme Classification Framework

Ahmed Mahran, Carlo Alessandro Borella, Konstantinos Perifanos

IIITH at SemEval-2022 Task 5: A comparative study of deep learning models for identifying misogynous memes

Tathagata Raha, Sagar Joshi, Vasudeva Varma

UniBO at SemEval-2022 Task 5: A Multimodal bi-Transformer Approach to the Binary and Fine-grained Identification of Misogyny in Memes

Arianna Muti, Katerina Korre, Alberto Barrón-Cedeño

MilaNLP at SemEval-2022 Task 5: Using Perceiver IO for Detecting Misogynous Memes with Text and Image Modalities

Giuseppe Attanasio, Debora Nozza, Federico Bianchi

taochen at SemEval-2022 Task 5: Multimodal Multitask Learning and Ensemble Learning

Chen Tao, Jung-jae Kim

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

Paridhi Maheshwari, Sharmila Reddy Nangi

RIT Boston at SemEval-2022 Task 5: Multimedia Misogyny Detection By Using Coherent Visual and Language Features from CLIP Model and Data-centric AI Principle

Lei Chen, Hou Wei Chou

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

Wentao Yu, Benedikt Boenninghoff, Jonas Röhrig, Dorothea Kolossa

UPB at SemEval-2022 Task 5: Enhancing UNITER with Image Sentiment and Graph Convolutional Networks for Multimedia Automatic Misogyny Identification

Andrei Paraschiv, Mihai Dascalu, Dumitru-Clementin Cercel

JRLV at SemEval-2022 Task 5: The Importance of Visual Elements for Misogyny Identification in Memes

Jason Ravagli, Lorenzo Vaiani

UAEM-ITAM at SemEval-2022 Task 5: Vision-Language Approach to Recognize Misogynous Content in Memes

Edgar Roman-Rangel, Jorge Fuentes-Pacheco, Jorge Hermosillo Valadez

ASRtrans at SemEval-2022 Task 5: Transformer-based Models for Meme Classification

Ailneni Rakshitha Rao, Arjun Rao

SRCB at SemEval-2022 Task 5: Pretraining Based Image to Text Late Sequential Fusion System for Multimodal Misogynous Meme Identification

Jing Zhang, Yujin Wang

HateU at SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification

Aymé Arango, Jesus Perez-Martin, Arniel Labrada

LastResort at SemEval-2022 Task 5: Towards Misogyny Identification using Visual Linguistic Model Ensembles And Task-Specific Pretraining

Samyak Agrawal, Radhika Mamidi

TechSSN at SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification using Deep Learning Models

Rajalakshmi Sivanaiah, Angel Deborah S, Sakaya Milton R, Mirnalinee T T

DD-TIG at SemEval-2022 Task 5: Investigating the Relationships Between Multimodal and Unimodal Information in Misogynous Memes Detection and Classification

Ziming Zhou, Han Zhao, Jingjing Dong, Ning Ding, Xiaolong Liu

PAIC at SemEval-2022 Task 5: Multi-Modal Misogynous Detection in MEMES with Multi-Task Learning And Multi-model Fusion

Jin Zhi, Zhou Mengyuan, Mengfei Yuan, Dou Hu, Xiyang Du

Transformers at SemEval-2022 Task 5: A Feature Extraction based Approach for Misogynous Meme Detection

Shankar Mahadevan, Sean Benhur, Roshan Nayak, Malliga Subramanian, Kogilavani Shanmugavadivel

SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification

Elisabetta Fersini, Francesca Gasparini, Giulia Rizzi, Aurora Saibene, Berta Chulvi

ULFRI at SemEval-2022 Task 4: Leveraging uncertainty and additional knowledge for patronizing and condescending language detection

Matej Klemen, Marko Robnik-Sikonja

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

Amrita_CEN at SemEval-2022 Task 4: Oversampling-based Machine Learning Approach for Detecting Patronizing and Condescending Language

Bichu George, Adarsh S, Nishitkumar Prajapati, Premjith B, Soman Kp

University of Bucharest Team at Semeval-2022 Task4: Detection and Classification of Patronizing and Condescending Language

Tudor Dumitrascu, Raluca-Andreea Gînga, Bogdan Dobre, Bogdan Radu Silviu Sielecki

CS/NLP at SemEval-2022 Task 4: Effective Data Augmentation Methods for Patronizing Language Detection and Multi-label Classification with RoBERTa and GPT3

Daniel Saeedi, Sirwe Saeedi, Aliakbar Panahi, Alvis C.M. Fong

Taygete at SemEval-2022 Task 4: RoBERTa based models for detecting Patronising and Condescending Language

Jayant Chhillar

SATLab at SemEval-2022 Task 4: Trying to Detect Patronizing and Condescending Language with only Character and Word N-grams

Yves Bestgen

Amsqr at SemEval-2022 Task 4: Towards AutoNLP via Meta-Learning and Adversarial Data Augmentation for PCL Detection

Alejandro Mosquera

Xu at SemEval-2022 Task 4: Pre-BERT Neural Network Methods vs Post-BERT RoBERTa Approach for Patronizing and Condescending Language Detection

Jinghua Xu

ML_LTU at SemEval-2022 Task 4: T5 Towards Identifying Patronizing and Condescending Language

Tosin Adewumi, Lama Alkhaled, Hamam Mokayed, Foteini Liwicki, Marcus Liwicki

PiCkLe at SemEval-2022 Task 4: Boosting Pre-trained Language Models with Task Specific Metadata and Cost Sensitive Learning

Manan Suri

I2C at SemEval-2022 Task 4: Patronizing and Condescending Language Detection using Deep Learning Techniques

Laura Vázquez Ramos, Adrián Moreno Monterde, Victoria Pachón, Jacinto Mata

YNU-HPCC at SemEval-2022 Task 4: Finetuning Pretrained Language Models for Patronizing and Condescending Language Detection

Wenqiang Bai, Jin Wang, Xuejie Zhang

UMass PCL at SemEval-2022 Task 4: Pre-trained Language Model Ensembles for Detecting Patronizing and Condescending Language

David Koleczek, Alexander Scarlatos, Preshma Linet Pereira, Siddha Makarand Karkare

HITMI&T at SemEval-2022 Task 4: Investigating Task-Adaptive Pretraining And Attention Mechanism On PCL Detection

Zihang Liu, Yancheng He, Feiqing Zhuang, Bing Xu

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

Junyu Lu, Hao Zhang, Tongyue Zhang, Hongbo Wang, Haohao Zhu

Team LRL_NC at SemEval-2022 Task 4: Binary and Multi-label Classification of PCL using Fine-tuned Transformer-based Models

Kushagri Tandon, Niladri Chatterjee

Team Stanford ACMLab at SemEval 2022 Task 4: Textual Analysis of PCL Using Contextual Word Embeddings

Upamanyu Dass-Vattam, Spencer Wallace, Rohan Sikand, Zach Witzel, Jillian Tang

McRock at SemEval-2022 Task 4: Patronizing and Condescending Language Detection using Multi-Channel CNN, Hybrid LSTM, DistilBERT and XLNet

Marco Siino, Marco Cascia, Ilenia Tinnirello

Sapphire at SemEval-2022 Task 4: A Patronizing and Condescending Language Detection Model Based on Capsule Networks

Sihui Li, Xiaobing Zhou

SSN_NLP_MLRG at SemEval-2022 Task 4: Ensemble Learning strategies to detect Patronizing and Condescending Language

Kalaivani Adaikkan, Thenmozhi Durairaj

Tesla at SemEval-2022 Task 4: Patronizing and Condescending Language Detection using Transformer-based Models with Data Augmentation

Sahil Bhatt, Manish Shrivastava

AliEdalat at SemEval-2022 Task 4: Patronizing and Condescending Language Detection using Fine-tuned Language Models, BERT+BiGRU, and Ensemble Models

Ali Edalat, Yadollah Yaghoobzadeh, Behnam Bahrak

UTSA NLP at SemEval-2022 Task 4: An Exploration of Simple Ensembles of Transformers, Convolutional, and Recurrent Neural Networks

Xingmeng Zhao, Anthony Rios

RNRE-NLP at SemEval-2022 Task 4: Patronizing and Condescending Language Detection

Rylan Yang, Ethan Chi, Nathan Chi

Team LEGO at SemEval-2022 Task 4: Machine Learning Methods for PCL Detection

Abhishek Singh

MS@IW at SemEval-2022 Task 4: Patronising and Condescending Language Detection with Synthetically Generated Data

Selina Meyer, Maximilian Schmidhuber, Udo Kruschwitz

Felix&Julia at SemEval-2022 Task 4: Patronizing and Condescending Language Detection

Felix Herrmann, Julia Krebs

LastResort at SemEval-2022 Task 4: Towards Patronizing and Condescending Language Detection using Pre-trained Transformer Based Models Ensembles

Samyak Agrawal, Radhika Mamidi

ASRtrans at SemEval-2022 Task 4: Ensemble of Tuned Transformer-based Models for PCL Detection

Ailneni Rakshitha Rao

PALI-NLP at SemEval-2022 Task 4: Discriminative Fine-tuning of Transformers for Patronizing and Condescending Language Detection

Dou Hu, Zhou Mengyuan, Xiyang Du, Mengfei Yuan, Jin Zhi

DH-FBK at SemEval-2022 Task 4: Leveraging Annotators’ Disagreement and Multiple Data Views for Patronizing Language Detection

Alan Ramponi, Elisa Leonardelli

BEIKE NLP at SemEval-2022 Task 4: Prompt-Based Paragraph Classification for Patronizing and Condescending Language Detection

Yong Deng, Chenxiao Dou, Liangyu Chen, Deqiang Miao, Xianghui Sun

PINGAN Omini-Sinitic at SemEval-2022 Task 4: Multi-prompt Training for Patronizing and Condescending Language Detection

Ye Wang, Yanmeng Wang, Baishun Ling, Zexiang Liao, Shaojun Wang

JUST-DEEP at SemEval-2022 Task 4: Using Deep Learning Techniques to Reveal Patronizing and Condescending Language

Mohammad Makahleh, Naba Bani Yaseen, Malak Abdullah

SemEval-2022 Task 4: Patronizing and Condescending Language Detection

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

HW-TSC at SemEval-2022 Task 3: A Unified Approach Fine-tuned on Multilingual Pretrained Model for PreTENS

Yinglu Li, Min Zhang, Xiaosong Qiao, Minghan Wang

KaMiKla at SemEval-2022 Task 3: AlBERTo, BERT, and CamemBERT—Be(r)tween Taxonomy Detection and Prediction

Karl Vetter, Miriam Segiet, Klara Lennermann

UU-Tax at SemEval-2022 Task 3: Improving the generalizability of language models for taxonomy classification through data augmentation

Injy Sarhan, Pablo Mosteiro, Marco Spruit

SPDB Innovation Lab at SemEval-2022 Task 3: Recognize Appropriate Taxonomic Relations Between Two Nominal Arguments with ERNIE-M Model

Yue Zhou, Bowei Wei, Jianyu Liu, Yang Yang