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SemEval 2022: all accepted papers

233 papers · page 3 of 3 · the most cited first · ← SemEval 2022

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  1. HiJoNLP at SemEval-2022 Task 2: Detecting Idiomaticity of Multiword Expressions using Multilingual Pretrained Language Models ↗Minghuan Tan
  2. I2C at SemEval-2022 Task 4: Patronizing and Condescending Language Detection using Deep Learning Techniques ↗Laura Vázquez Ramos, Adrián Moreno Monterde, Victoria Pachón et al.
  3. ISD at SemEval-2022 Task 6: Sarcasm Detection Using Lightweight ModelsSamantha Huang, Ethan Chi, Nathan Chiour summary
  4. JBNU-CCLab at SemEval-2022 Task 7: DeBERTa for Identifying Plausible Clarifications in Instructional Texts ↗Daewook Kang, Sung-Min Lee, Eunhwan Park et al.
  5. 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
  6. JUST-DEEP at SemEval-2022 Task 4: Using Deep Learning Techniques to Reveal Patronizing and Condescending Language ↗Mohammad Makahleh, Naba Bani Yaseen, Malak Abdullah
  7. LSX_team5 at SemEval-2022 Task 8: Multilingual News Article Similarity Assessment based on Word- and Sentence Mover's Distance ↗Stefan Heil, Karina Kopp, Albin Zehe et al.
  8. MS@IW at SemEval-2022 Task 4: Patronising and Condescending Language Detection with Synthetically Generated Data ↗Selina Meyer, Maximilian Schmidhuber, Udo Kruschwitz
  9. PA Ph&Tech at SemEval-2022 Task 11: NER Task with Ensemble Embedding from Reinforcement Learning ↗Qizhi Lin, Changyu Hou, Xiaopeng Wang et al.
  10. PALI at SemEval-2022 Task 7: Identifying Plausible Clarifications of Implicit and Underspecified Phrases in Instructional Texts ↗Zhou Mengyuan, Dou Hu, Mengfei Yuan et al.
  11. PINGAN_AI at SemEval-2022 Task 9: Recipe knowledge enhanced model applied in Competence-based Multimodal Question Answering ↗Zhihao Ruan, Xiaolong Hou, Lianxin Jiang
  12. RNRE-NLP at SemEval-2022 Task 4: Patronizing and Condescending Language Detection ↗Rylan Yang, Ethan Chi, Nathan Chi
  13. SATLab at SemEval-2022 Task 4: Trying to Detect Patronizing and Condescending Language with only Character and Word N-grams ↗Yves Bestgen
  14. SLPL-Sentiment at SemEval-2022 Task 10: Making Use of Pre-Trained Model's Attention Values in Structured Sentiment Analysis ↗Sadrodin Barikbin
  15. SPDB Innovation Lab at SemEval-2022 Task 10: A Novel End-to-End Structured Sentiment Analysis Model based on the ERNIE-M ↗Yalong Jia, Zhenghui Ou, Yang Yang
  16. SSN_MLRG1 at SemEval-2022 Task 10: Structured Sentiment Analysis using 2-layer BiLSTM ↗Karun Anantharaman, Divyasri K, Jayannthan Pt et al.
  17. SSN_NLP_MLRG at SemEval-2022 Task 4: Ensemble Learning strategies to detect Patronizing and Condescending Language ↗Kalaivani Adaikkan, Thenmozhi Durairaj
  18. Sapphire at SemEval-2022 Task 4: A Patronizing and Condescending Language Detection Model Based on Capsule Networks ↗Sihui Li, Xiaobing Zhou
  19. SenPoi at SemEval-2022 Task 10: Point me to your Opinion, SenPoi ↗Jan Pfister, Sebastian Wankerl, Andreas Hotho
  20. SkoltechNLP at SemEval-2022 Task 8: Multilingual News Article Similarity via Exploration of News Texts to Vector Representations ↗Mikhail Kuimov, Daryna Dementieva, Alexander Panchenko
  21. Sliced at SemEval-2022 Task 11: Bigger, Better? Massively Multilingual LMs for Multilingual Complex NER on an Academic GPU Budget ↗Barbara Plank
  22. Stanford MLab at SemEval 2022 Task 7: Tree- and Transformer-Based Methods for Clarification Plausibility ↗Thomas Yim, Junha Lee, Rishi Verma et al.
  23. Taygete at SemEval-2022 Task 4: RoBERTa based models for detecting Patronising and Condescending Language ↗Jayant Chhillar
  24. Team LEGO at SemEval-2022 Task 4: Machine Learning Methods for PCL Detection ↗Abhishek Singh
  25. Team Stanford ACMLab at SemEval 2022 Task 4: Textual Analysis of PCL Using Contextual Word Embeddings ↗Upamanyu Dass-Vattam, Spencer Wallace, Rohan Sikand et al.
  26. Team TMA at SemEval-2022 Task 8: Lightweight and Language-Agnostic News Similarity Classifier ↗Nicolas Stefanovitch
  27. Team dina at SemEval-2022 Task 8: Pre-trained Language Models as Baselines for Semantic Similarity ↗Dina Pisarevskaya, Arkaitz Zubiaga
  28. TechSSN at SemEval-2022 Task 6: Intended Sarcasm Detection using Transformer ModelsRajalakshmi Sivanaiah, Angel Deborah S, Sakaya Milton R et al.our summary
  29. UMUTeam at SemEval-2022 Task 6: Evaluating Transformers for detecting Sarcasm in English and Arabic ↗José García-Díaz, Camilo Caparros-Laiz, Rafael Valencia-García
  30. 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 et al.
  31. University of Bucharest Team at Semeval-2022 Task4: Detection and Classification of Patronizing and Condescending Language ↗Tudor Dumitrascu, Raluca-Andreea Gînga, Bogdan Dobre et al.
  32. niksss at SemEval-2022 Task 6: Are Traditionally Pre-Trained Contextual Embeddings Enough for Detecting Intended Sarcasm ?Nikhil Singhour summary
  33. niksss at SemEval-2022 Task7:Transformers for Grading the Clarifications on Instructional Texts ↗Nikhil Singh

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