---
title: "SemEval 2022 — all accepted papers, page 3 — Elamur Research"
description: "All 233 papers of SemEval 2022 · page 3 of 3, the most cited first; those with our summary link to it."
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# SemEval 2022: all accepted papers

233 papers · page 3 of 3 · the most cited first · [← SemEval 2022](https://md.research.elamur.ai/free/en/venues/semeval/2022/)

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201. **[HiJoNLP at SemEval-2022 Task 2: Detecting Idiomaticity of Multiword Expressions using Multilingual Pretrained Language Models ↗](https://aclanthology.org/2022.semeval-1.23/)**Minghuan Tan
202. **[I2C at SemEval-2022 Task 4: Patronizing and Condescending Language Detection using Deep Learning Techniques ↗](https://aclanthology.org/2022.semeval-1.62/)**Laura Vázquez Ramos, Adrián Moreno Monterde, Victoria Pachón et al.
203. **[ISD at SemEval-2022 Task 6: Sarcasm Detection Using Lightweight Models](https://md.research.elamur.ai/free/en/papers/huang-2022-isd-semeval-2022-task-6/)**Samantha Huang, Ethan Chi, Nathan Chi*our summary*
204. **[JBNU-CCLab at SemEval-2022 Task 7: DeBERTa for Identifying Plausible Clarifications in Instructional Texts ↗](https://aclanthology.org/2022.semeval-1.147/)**Daewook Kang, Sung-Min Lee, Eunhwan Park et al.
205. **[JCT at SemEval-2022 Task 4-A: Patronism Detection in Posts Written in English using Preprocessing Methods and various Machine Leaerning Methods ↗](https://aclanthology.org/2022.semeval-1.72/)**Yaakov HaCohen-Kerner, Ilan Meyrowitsch, Matan Fchima
206. **[JUST-DEEP at SemEval-2022 Task 4: Using Deep Learning Techniques to Reveal Patronizing and Condescending Language ↗](https://aclanthology.org/2022.semeval-1.39/)**Mohammad Makahleh, Naba Bani Yaseen, Malak Abdullah
207. **[LSX_team5 at SemEval-2022 Task 8: Multilingual News Article Similarity Assessment based on Word- and Sentence Mover's Distance ↗](https://aclanthology.org/2022.semeval-1.168/)**Stefan Heil, Karina Kopp, Albin Zehe et al.
208. **[MS@IW at SemEval-2022 Task 4: Patronising and Condescending Language Detection with Synthetically Generated Data ↗](https://aclanthology.org/2022.semeval-1.47/)**Selina Meyer, Maximilian Schmidhuber, Udo Kruschwitz
209. **[PA Ph&Tech at SemEval-2022 Task 11: NER Task with Ensemble Embedding from Reinforcement Learning ↗](https://aclanthology.org/2022.semeval-1.198/)**Qizhi Lin, Changyu Hou, Xiaopeng Wang et al.
210. **[PALI at SemEval-2022 Task 7: Identifying Plausible Clarifications of Implicit and Underspecified Phrases in Instructional Texts ↗](https://aclanthology.org/2022.semeval-1.153/)**Zhou Mengyuan, Dou Hu, Mengfei Yuan et al.
211. **[PINGAN_AI at SemEval-2022 Task 9: Recipe knowledge enhanced model applied in Competence-based Multimodal Question Answering ↗](https://aclanthology.org/2022.semeval-1.179/)**Zhihao Ruan, Xiaolong Hou, Lianxin Jiang
212. **[RNRE-NLP at SemEval-2022 Task 4: Patronizing and Condescending Language Detection ↗](https://aclanthology.org/2022.semeval-1.49/)**Rylan Yang, Ethan Chi, Nathan Chi
213. **[SATLab at SemEval-2022 Task 4: Trying to Detect Patronizing and Condescending Language with only Character and Word N-grams ↗](https://aclanthology.org/2022.semeval-1.67/)**Yves Bestgen
214. **[SLPL-Sentiment at SemEval-2022 Task 10: Making Use of Pre-Trained Model's Attention Values in Structured Sentiment Analysis ↗](https://aclanthology.org/2022.semeval-1.192/)**Sadrodin Barikbin
215. **[SPDB Innovation Lab at SemEval-2022 Task 10: A Novel End-to-End Structured Sentiment Analysis Model based on the ERNIE-M ↗](https://aclanthology.org/2022.semeval-1.194/)**Yalong Jia, Zhenghui Ou, Yang Yang
216. **[SSN_MLRG1 at SemEval-2022 Task 10: Structured Sentiment Analysis using 2-layer BiLSTM ↗](https://aclanthology.org/2022.semeval-1.184/)**Karun Anantharaman, Divyasri K, Jayannthan Pt et al.
217. **[SSN_NLP_MLRG at SemEval-2022 Task 4: Ensemble Learning strategies to detect Patronizing and Condescending Language ↗](https://aclanthology.org/2022.semeval-1.53/)**Kalaivani Adaikkan, Thenmozhi Durairaj
218. **[Sapphire at SemEval-2022 Task 4: A Patronizing and Condescending Language Detection Model Based on Capsule Networks ↗](https://aclanthology.org/2022.semeval-1.54/)**Sihui Li, Xiaobing Zhou
219. **[SenPoi at SemEval-2022 Task 10: Point me to your Opinion, SenPoi ↗](https://aclanthology.org/2022.semeval-1.183/)**Jan Pfister, Sebastian Wankerl, Andreas Hotho
220. **[SkoltechNLP at SemEval-2022 Task 8: Multilingual News Article Similarity via Exploration of News Texts to Vector Representations ↗](https://aclanthology.org/2022.semeval-1.160/)**Mikhail Kuimov, Daryna Dementieva, Alexander Panchenko
221. **[Sliced at SemEval-2022 Task 11: Bigger, Better? Massively Multilingual LMs for Multilingual Complex NER on an Academic GPU Budget ↗](https://aclanthology.org/2022.semeval-1.205/)**Barbara Plank
222. **[Stanford MLab at SemEval 2022 Task 7: Tree- and Transformer-Based Methods for Clarification Plausibility ↗](https://aclanthology.org/2022.semeval-1.150/)**Thomas Yim, Junha Lee, Rishi Verma et al.
223. **[Taygete at SemEval-2022 Task 4: RoBERTa based models for detecting Patronising and Condescending Language ↗](https://aclanthology.org/2022.semeval-1.68/)**Jayant Chhillar
224. **[Team LEGO at SemEval-2022 Task 4: Machine Learning Methods for PCL Detection ↗](https://aclanthology.org/2022.semeval-1.48/)**Abhishek Singh
225. **[Team Stanford ACMLab at SemEval 2022 Task 4: Textual Analysis of PCL Using Contextual Word Embeddings ↗](https://aclanthology.org/2022.semeval-1.56/)**Upamanyu Dass-Vattam, Spencer Wallace, Rohan Sikand et al.
226. **[Team TMA at SemEval-2022 Task 8: Lightweight and Language-Agnostic News Similarity Classifier ↗](https://aclanthology.org/2022.semeval-1.166/)**Nicolas Stefanovitch
227. **[Team dina at SemEval-2022 Task 8: Pre-trained Language Models as Baselines for Semantic Similarity ↗](https://aclanthology.org/2022.semeval-1.169/)**Dina Pisarevskaya, Arkaitz Zubiaga
228. **[TechSSN at SemEval-2022 Task 6: Intended Sarcasm Detection using Transformer Models](https://md.research.elamur.ai/free/en/papers/sivanaiah-2022-techssn-semeval-2022-task-6/)**Rajalakshmi Sivanaiah, Angel Deborah S, Sakaya Milton R et al.*our summary*
229. **[UMUTeam at SemEval-2022 Task 6: Evaluating Transformers for detecting Sarcasm in English and Arabic ↗](https://aclanthology.org/2022.semeval-1.142/)**José García-Díaz, Camilo Caparros-Laiz, Rafael Valencia-García
230. **[UMass PCL at SemEval-2022 Task 4: Pre-trained Language Model Ensembles for Detecting Patronizing and Condescending Language ↗](https://aclanthology.org/2022.semeval-1.60/)**David Koleczek, Alexander Scarlatos, Preshma Linet Pereira et al.
231. **[University of Bucharest Team at Semeval-2022 Task4: Detection and Classification of Patronizing and Condescending Language ↗](https://aclanthology.org/2022.semeval-1.70/)**Tudor Dumitrascu, Raluca-Andreea Gînga, Bogdan Dobre et al.
232. **[niksss at SemEval-2022 Task 6: Are Traditionally Pre-Trained Contextual Embeddings Enough for Detecting Intended Sarcasm ?](https://md.research.elamur.ai/free/en/papers/singh-2022-niksss-semeval-2022-task-6/)**Nikhil Singh*our summary*
233. **[niksss at SemEval-2022 Task7:Transformers for Grading the Clarifications on Instructional Texts ↗](https://aclanthology.org/2022.semeval-1.154/)**Nikhil Singh

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