Table of Contents

• SemEval-2020 Task 1: Unsupervised Lexical Semantic Change DetectionDominik Schlechtweg, Barbara McGillivray, Simon Hengchen, Haim Dubossarsky, Nina Tahmasebi. 1-23 [doi]
• SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical EntailmentGoran Glavas, Ivan Vulic, Anna Korhonen, Simone Paolo Ponzetto. 24-35 [doi]
• SemEval-2020 Task 3: Graded Word Similarity in ContextCarlos Santos Armendariz, Matthew Purver, Senja Pollak, Nikola Ljubesic, Matej Ulcar, Ivan Vulic, Mohammad Taher Pilehvar. 36-49 [doi]
• DiaSense at SemEval-2020 Task 1: Modeling Sense Change via Pre-trained BERT EmbeddingsChristin Beck. 50-58 [doi]
• BabelEnconding at SemEval-2020 Task 3: Contextual Similarity as a Combination of Multilingualism and Language ModelsLucas Rafael Costella Pessutto, Tiago de Melo, Viviane P. Moreira, Altigran Soares da Silva. 59-66 [doi]
• Discovery Team at SemEval-2020 Task 1: Context-sensitive Embeddings Not Always Better than Static for Semantic Change DetectionMatej Martinc, Syrielle Montariol, Elaine Zosa, Lidia Pivovarova. 67-73 [doi]
• GM-CTSC at SemEval-2020 Task 1: Gaussian Mixtures Cross Temporal Similarity ClusteringPierluigi Cassotti, Annalina Caputo, Marco Polignano, Pierpaolo Basile. 74-80 [doi]
• IMS at SemEval-2020 Task 1: How Low Can You Go? Dimensionality in Lexical Semantic Change DetectionJens Kaiser, Dominik Schlechtweg, Sean Papay, Sabine Schulte im Walde. 81-89 [doi]
• JCT at SemEval-2020 Task 1: Combined Semantic Vector Spaces Models for Unsupervised Lexical Semantic Change DetectionEfrat Amar, Chaya Liebeskind. 90-97 [doi]
• RIJP at SemEval-2020 Task 1: Gaussian-based Embeddings for Semantic Change DetectionRan Iwamoto, Masahiro Yukawa. 98-104 [doi]
• SChME at SemEval-2020 Task 1: A Model Ensemble for Detecting Lexical Semantic ChangeMaurício Gruppi, Sibel Adali, Pin-Yu Chen. 105-111 [doi]
• SenseCluster at SemEval-2020 Task 1: Unsupervised Lexical Semantic Change DetectionAmaru Cuba Gyllensten, Evangelia Gogoulou, Ariel Ekgren, Magnus Sahlgren. 112-118 [doi]
• The UCD-Net System at SemEval-2020 Task 1: Temporal Referencing with Semantic Network DistancesPaul Nulty, David Lillis. 119-125 [doi]
• UiO-UvA at SemEval-2020 Task 1: Contextualised Embeddings for Lexical Semantic Change DetectionAndrey Kutuzov, Mario Giulianelli. 126-134 [doi]
• BMEAUT at SemEval-2020 Task 2: Lexical Entailment with Semantic GraphsÁdám Kovács, Kinga Gémes, András Kornai, Gábor Recski. 135-141 [doi]
• BRUMS at SemEval-2020 Task 3: Contextualised Embeddings for Predicting the (Graded) Effect of Context in Word SimilarityHansi Hettiarachchi, Tharindu Ranasinghe. 142-149 [doi]
• MineriaUNAM at SemEval-2020 Task 3: Predicting Contextual WordSimilarity Using a Centroid Based Approach and Word EmbeddingsHelena Gómez-Adorno, Gemma Bel Enguix, Jorge Reyes-Magaña, Benjamín Moreno, Ramón Casillas, Daniel Vargas. 150-157 [doi]
• MULTISEM at SemEval-2020 Task 3: Fine-tuning BERT for Lexical MeaningAina Garí Soler, Marianna Apidianaki. 158-165 [doi]
• UZH at SemEval-2020 Task 3: Combining BERT with WordNet Sense Embeddings to Predict Graded Word Similarity ChangesLi Tang. 166-170 [doi]
• BOS at SemEval-2020 Task 1: Word Sense Induction via Lexical Substitution for Lexical Semantic Change DetectionNikolay Arefyev, Vasily Zhikov. 171-179 [doi]
• CIRCE at SemEval-2020 Task 1: Ensembling Context-Free and Context-Dependent Word RepresentationsMartin Pömsl, Roman Lyapin. 180-186 [doi]
• CMCE at SemEval-2020 Task 1: Clustering on Manifolds of Contextualized Embeddings to Detect Historical Meaning ShiftsDavid Rother, Thomas N. Haider, Steffen Eger. 187-193 [doi]
• DCC-Uchile at SemEval-2020 Task 1: Temporal Referencing Word EmbeddingsFrank D. Zamora-Reina, Felipe Bravo-Marquez. 194-200 [doi]
• EmbLexChange at SemEval-2020 Task 1: Unsupervised Embedding-based Detection of Lexical Semantic ChangesEhsaneddin Asgari, Christoph Ringlstetter, Hinrich Schütze. 201-207 [doi]
• GloVeInit at SemEval-2020 Task 1: Using GloVe Vector Initialization for Unsupervised Lexical Semantic Change DetectionVaibhav Jain. 208-213 [doi]
• SST-BERT at SemEval-2020 Task 1: Semantic Shift Tracing by Clustering in BERT-based Embedding SpacesVani Kanjirangat, Sandra Mitrovic, Alessandro Antonucci, Fabio Rinaldi 0001. 214-221 [doi]
• TemporalTeller at SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection with Temporal ReferencingJinan Zhou, Jiaxin Li. 222-231 [doi]
• TUE at SemEval-2020 Task 1: Detecting Semantic Change by Clustering Contextual Word EmbeddingsAnna Karnysheva, Pia Schwarz. 232-238 [doi]
• UoB at SemEval-2020 Task 1: Automatic Identification of Novel Word SensesEleri Sarsfield, Harish Tayyar Madabushi. 239-245 [doi]
• UWB at SemEval-2020 Task 1: Lexical Semantic Change DetectionOndrej Prazák, Pavel Pribán, Stephen Taylor 0001, Jakub Sido. 246-254 [doi]
• SHIKEBLCU at SemEval-2020 Task 2: An External Knowledge-enhanced Matrix for Multilingual and Cross-Lingual Lexical EntailmentShike Wang, Yuchen Fan, Xiangying Luo, Dong Yu. 255-262 [doi]
• UAlberta at SemEval-2020 Task 2: Using Translations to Predict Cross-Lingual EntailmentBradley Hauer, Amir Ahmad Habibi, Yixing Luan, Arnob Mallik, Grzegorz Kondrak. 263-269 [doi]
• AlexU-AUX-BERT at SemEval-2020 Task 3: Improving BERT Contextual Similarity Using Multiple Auxiliary ContextsMahmoud S. Abdel-Majeed, Marwan Torki. 270-274 [doi]
• CitiusNLP at SemEval-2020 Task 3: Comparing Two Approaches for Word Vector ContextualizationPablo Gamallo 0001. 275-280 [doi]
• Ferryman at SemEval-2020 Task 3: Bert with TFIDF-Weighting for Predicting the Effect of Context in Word SimilarityWeilong Chen, Xin Yuan, Sai Zhang, Jiehui Wu, Yanru Zhang, Yan Wang. 281-285 [doi]
• Hitachi at SemEval-2020 Task 3: Exploring the Representation Spaces of Transformers for Human Sense Word SimilarityTerufumi Morishita, Gaku Morio, Hiroaki Ozaki, Toshinori Miyoshi. 286-291 [doi]
• JUSTMasters at SemEval-2020 Task 3: Multilingual Deep Learning Model to Predict the Effect of Context in Word SimilarityNour Al-Khdour, Mutaz Bni Younes, Malak Abdullah, Mohammad Al-Smadi. 292-300 [doi]
• Will_Go at SemEval-2020 Task 3: An Accurate Model for Predicting the (Graded) Effect of Context in Word Similarity Based on BERTWei Bao, Hongshu Che, Jiandong zhang. 301-306 [doi]
• SemEval-2020 Task 4: Commonsense Validation and ExplanationCunxiang Wang, Shuailong Liang, Yili Jin, Yilong Wang, Xiaodan Zhu, Yue Zhang. 307-321 [doi]
• SemEval-2020 Task 5: Counterfactual RecognitionXiaoyu Yang, Stephen Obadinma, Huasha Zhao, Qiong Zhang, Stan Matwin, Xiaodan Zhu. 322-335 [doi]
• SemEval-2020 Task 6: Definition Extraction from Free Text with the DEFT CorpusSasha Spala, Nicholas A. Miller, Franck Dernoncourt, Carl Dockhorn. 336-345 [doi]
• IIE-NLP-NUT at SemEval-2020 Task 4: Guiding PLM with Prompt Template Reconstruction Strategy for ComVELuxi Xing, Yuqiang Xie, Yue Hu 0002, Wei Peng. 346-353 [doi]
• HIT-SCIR at SemEval-2020 Task 5: Training Pre-trained Language Model with Pseudo-labeling Data for Counterfactuals DetectionXiao Ding, Dingkui Hao, Yuewei Zhang, Kuo Liao, Zhongyang Li, Bing Qin 0001, Ting Liu 0001. 354-360 [doi]
• Cardiff University at SemEval-2020 Task 6: Fine-tuning BERT for Domain-Specific Definition ClassificationShelan S. Jeawak, Luis Espinosa Anke, Steven Schockaert. 361-366 [doi]
• ANA at SemEval-2020 Task 4: MUlti-task learNIng for cOmmonsense reasoNing (UNION)Anandh Konar, Chenyang Huang 0001, Amine Trabelsi, Osmar R. Zaïane. 367-373 [doi]
• BUT-FIT at SemEval-2020 Task 4: Multilingual CommonsenseJosef Jon, Martin Fajcik, Martin Docekal, Pavel Smrz. 374-390 [doi]
• CUHK at SemEval-2020 Task 4: CommonSense Explanation, Reasoning and Prediction with Multi-task LearningHongru Wang 0003, Xiangru Tang, Sunny Lai, Kwong-Sak Leung, Jia Zhu, Gabriel Pui Cheong Fung, Kam-Fai Wong. 391-400 [doi]
• ECNU-SenseMaker at SemEval-2020 Task 4: Leveraging Heterogeneous Knowledge Resources for Commonsense Validation and ExplanationQian Zhao, Siyu Tao, Jie Zhou 0015, Linlin Wang, Xin Lin, Liang He 0001. 401-410 [doi]
• Masked Reasoner at SemEval-2020 Task 4: Fine-Tuning RoBERTa for Commonsense ReasoningDaming Lu. 411-414 [doi]
• QiaoNing at SemEval-2020 Task 4: Commonsense Validation and Explanation System Based on Ensemble of Language ModelLiu Pai. 415-421 [doi]
• SWAGex at SemEval-2020 Task 4: Commonsense Explanation as Next Event PredictionWiem Ben Rim, Naoaki Okazaki. 422-429 [doi]
• UoR at SemEval-2020 Task 4: Pre-trained Sentence Transformer Models for Commonsense Validation and ExplanationThanet Markchom, Bhuvana Dhruva, Chandresh Pravin, Huizhi Liang. 430-436 [doi]
• BUT-FIT at SemEval-2020 Task 5: Automatic Detection of Counterfactual Statements with Deep Pre-trained Language Representation ModelsMartin Fajcik, Josef Jon, Martin Docekal, Pavel Smrz. 437-444 [doi]
• CLaC at SemEval-2020 Task 5: Muli-task Stacked Bi-LSTMsMinGyou Sung, Parsa Bagherzadeh, Sabine Bergler. 445-450 [doi]
• CNRL at SemEval-2020 Task 5: Modelling Causal Reasoning in Language with Multi-Head Self-Attention Weights Based Counterfactual DetectionRajaswa Patil, Veeky Baths. 451-457 [doi]
• IITK-RSA at SemEval-2020 Task 5: Detecting CounterfactualsAnirudh Anil Ojha, Rohin Garg, Shashank Gupta 0008, Ashutosh Modi. 458-467 [doi]
• Yseop at SemEval-2020 Task 5: Cascaded BERT Language Model for Counterfactual Statement AnalysisHanna Abi Akl, Dominique Mariko, Estelle Labidurie. 468-478 [doi]
• ACNLP at SemEval-2020 Task 6: A Supervised Approach for Definition ExtractionFabien Caspani, Pirashanth Ratnamogan, Mathis Linger, Mhamed Hajaiej. 479-486 [doi]
• Gorynych Transformer at SemEval-2020 Task 6: Multi-task Learning for Definition ExtractionAdis Davletov, Nikolay Arefyev, Alexander Shatilov, Denis Gordeev, Alexey Rey. 487-493 [doi]
• CN-HIT-IT.NLP at SemEval-2020 Task 4: Enhanced Language Representation with Multiple Knowledge TriplesYice Zhang, Jiaxuan Lin, Yang Fan, Peng Jin, Yuanchao Liu, Bingquan Liu. 494-500 [doi]
• CS-NET at SemEval-2020 Task 4: Siamese BERT for ComVESoumya Ranjan Dash, Sandeep Routray, Prateek Varshney, Ashutosh Modi. 501-506 [doi]
• CS-NLP Team at SemEval-2020 Task 4: Evaluation of State-of-the-art NLP Deep Learning Architectures on Commonsense Reasoning TaskSirwe Saeedi, Aliakbar Panahi, Seyran Saeedi, Alvis Cheuk Ming Fong. 507-515 [doi]
• DEEPYANG at SemEval-2020 Task 4: Using the Hidden Layer State of BERT Model for Differentiating Common SenseYang Bai, Xiaobing Zhou. 516-520 [doi]
• HR@JUST Team at SemEval-2020 Task 4: The Impact of RoBERTa Transformer for Evaluation Common Sense UnderstandingHeba Al-Jarrah, Rahaf Al-hamouri, Mohammad Al-Smadi. 521-526 [doi]
• JBNU at SemEval-2020 Task 4: BERT and UniLM for Commonsense Validation and ExplanationSeung-Hoon Na, Jong-Hyeok Lee. 527-534 [doi]
• JUSTers at SemEval-2020 Task 4: Evaluating Transformer Models against Commonsense Validation and ExplanationAli Fadel, Mahmoud Al-Ayyoub, Erik Cambria. 535-542 [doi]
• KaLM at SemEval-2020 Task 4: Knowledge-aware Language Models for Comprehension and GenerationJiajing Wan, Xinting Huang. 543-550 [doi]
• KDE SenseForce at SemEval-2020 Task 4: Exploiting BERT for Commonsense Validation and ExplanationKhanddorj Mendbayar, Masaki Aono. 551-555 [doi]
• Lijunyi at SemEval-2020 Task 4: An ALBERT Model Based Maximum Ensemble with Different Training Sizes and Depths for Commonsense Validation and ExplanationJunyi Li, Bin Wang, Haiyan Ding. 556-561 [doi]
• LMVE at SemEval-2020 Task 4: Commonsense Validation and Explanation Using Pretraining Language ModelShilei Liu, Yu Guo, Bochao Li, Feiliang Ren. 562-568 [doi]
• Mxgra at SemEval-2020 Task 4: Common Sense Making with Next Token PredictionKris Collins, Max Grathwohl, Heba Ahmed. 569-573 [doi]
• NLP@JUST at SemEval-2020 Task 4: Ensemble Technique for BERT and Roberta to Evaluate Commonsense ValidationEmran Al-Bashabsheh, Ayah Abu Aqouleh, Mohammad Al-Smadi. 574-579 [doi]
• SSN-NLP at SemEval-2020 Task 4: Text Classification and Generation on Common Sense Context Using Neural NetworksRishivardhan K, Kayalvizhi S, Thenmozhi D, Raghav R., Kshitij Sharma. 580-584 [doi]
• Team Solomon at SemEval-2020 Task 4: Be Reasonable: Exploiting Large-scale Language Models for Commonsense ReasoningVertika Srivastava, Sudeep Kumar Sahoo, Yeon Hyang Kim, Rohit R. R, Mayank Raj, Ajay Jaiswal. 585-593 [doi]
• TeamJUST at SemEval-2020 Task 4: Commonsense Validation and Explanation Using Ensembling TechniquesRoweida Mohammed, Malak Abdullah. 594-600 [doi]
• TR at SemEval-2020 Task 4: Exploring the Limits of Language-model-based Common Sense ValidationDon Teo. 601-608 [doi]
• UAICS at SemEval-2020 Task 4: Using a Bidirectional Transformer for Task aCiprian-Gabriel Cusmuliuc, Lucia Georgiana Coca, Adrian Iftene. 609-613 [doi]
• UI at SemEval-2020 Task 4: Commonsense Validation and Explanation by Exploiting ContradictionKerenza Doxolodeo, Rahmad Mahendra. 614-619 [doi]
• Warren at SemEval-2020 Task 4: ALBERT and Multi-Task Learning for Commonsense ValidationYuhang Wu, Hao Wu. 620-625 [doi]
• YNU-oxz at SemEval-2020 Task 4: Commonsense Validation Using BERT with Bidirectional GRUXiaozhi Ou, Hongling Li. 626-632 [doi]
• BLCU-NLP at SemEval-2020 Task 5: Data Augmentation for Efficient Counterfactual DetectingChang Liu, Dong Yu. 633-639 [doi]
• BYteam at SemEval-2020 Task 5: Detecting Counterfactual Statements with BERT and EnsemblesYang Bai, Xiaobing Zhou. 640-644 [doi]
• ETHAN at SemEval-2020 Task 5: Modelling Causal Reasoning in Language Using Neuro-symbolic Cloud ComputingLen Yabloko. 645-652 [doi]
• Ferryman as SemEval-2020 Task 5: Optimized BERT for Detecting CounterfactualsWeilong Chen, Yan Zhuang, Peng Wang 0082, Feng Hong, Yan Wang, Yanru Zhang. 653-657 [doi]
• ISCAS at SemEval-2020 Task 5: Pre-trained Transformers for Counterfactual Statement ModelingYaojie Lu 0001, Annan Li, Hongyu Lin, Xianpei Han, Le Sun 0001. 658-663 [doi]
• Lee at SemEval-2020 Task 5: ALBERT Model Based on the Maximum Ensemble Strategy and Different Data Sampling Methods for Detecting Counterfactual StatementsJunyi Li, Yuhang Wu, Bin Wang, Haiyan Ding. 664-669 [doi]
• NLU-Co at SemEval-2020 Task 5: NLU/SVM Based Model Apply Tocharacterise and Extract Counterfactual Items on Raw DataElvis Mboning Tchiaze, Damien Nouvel. 670-676 [doi]
• Pheonix at SemEval-2020 Task 5: Masking the Labels Lubricates Models for Sequence LabelingPouria Babvey, Dario Borrelli, Yutong Zhao, Carlo Lipizzi. 677-682 [doi]
• YNU-oxz at SemEval-2020 Task 5: Detecting Counterfactuals Based on Ordered Neurons LSTM and Hierarchical Attention NetworkXiaozhi Ou, Shengyan Liu, Hongling Li. 683-689 [doi]
• BERTatDE at SemEval-2020 Task 6: Extracting Term-definition Pairs in Free Text Using Pre-trained ModelHuiHui Zhang, Feiliang Ren. 690-696 [doi]
• DeftPunk at SemEval-2020 Task 6: Using RNN-ensemble for the Sentence ClassificationJekaterina Kaparina, Anna Soboleva. 697-703 [doi]
• Defx at SemEval-2020 Task 6: Joint Extraction of Concepts and Relations for Definition ExtractionMarc Hübner, Christoph Alt, Robert Schwarzenberg, Leonhard Hennig. 704-709 [doi]
• DSC IIT-ISM at SemEval-2020 Task 6: Boosting BERT with Dependencies for Definition ExtractionAadarsh Singh, Priyanshu Kumar, Aman Sinha. 710-716 [doi]
• RGCL at SemEval-2020 Task 6: Neural Approaches to DefinitionExtractionTharindu Ranasinghe, Alistair Plum, Constantin Orasan, Ruslan Mitkov. 717-723 [doi]
• TüKaPo at SemEval-2020 Task 6: Def(n)tly Not BERT: Definition Extraction Using pre-BERT Methods in a post-BERT WorldMadeeswaran Kannan, Haemanth Santhi Ponnusamy. 724-729 [doi]
• UNIXLONG at SemEval-2020 Task 6: A Joint Model for Definition ExtractionShu Yi Xie, Jian Ma, Haiqin Yang, Lian-Xin Jiang, Yang Mo, Jian-Ping Shen. 730-736 [doi]
• UPB at SemEval-2020 Task 6: Pretrained Language Models for Definition ExtractionAndrei-Marius Avram, Dumitru-Clementin Cercel, Costin-Gabriel Chiru. 737-745 [doi]
• SemEval-2020 Task 7: Assessing Humor in Edited News HeadlinesNabil Hossain, John Krumm, Michael Gamon, Henry A. Kautz. 746-758 [doi]
• SemEval-2020 Task 8: Memotion Analysis- the Visuo-Lingual Metaphor!Chhavi Sharma, Deepesh Bhageria, William Scott, PYKL Srinivas, Amitava Das, Tanmoy Chakraborty 0002, Viswanath Pulabaigari, Björn Gambäck. 759-773 [doi]
• SemEval-2020 Task 9: Overview of Sentiment Analysis of Code-Mixed TweetsParth Patwa, Gustavo Aguilar, Sudipta Kar, Suraj Pandey, PYKL Srinivas, Björn Gambäck, Tanmoy Chakraborty 0002, Thamar Solorio, Amitava Das. 774-790 [doi]
• Hitachi at SemEval-2020 Task 7: Stacking at Scale with Heterogeneous Language Models for Humor RecognitionTerufumi Morishita, Gaku Morio, Hiroaki Ozaki, Toshinori Miyoshi. 791-803 [doi]
• SESAM at SemEval-2020 Task 8: Investigating the Relationship between Image and Text in Sentiment Analysis of MemesLisa Bonheme, Marek Grzes. 804-816 [doi]
• Kk2018 at SemEval-2020 Task 9: Adversarial Training for Code-Mixing Sentiment ClassificationJiaxiang Liu 0004, Xuyi Chen, Shikun Feng, Shuohuan Wang, Xuan Ouyang, Yu Sun, Zhengjie Huang, Weiyue Su. 817-823 [doi]
• Buhscitu at SemEval-2020 Task 7: Assessing Humour in Edited News Headlines Using Hand-Crafted Features and Online Knowledge BasesKristian Nørgaard Jensen, Nicolaj Filrup Rasmussen, Thai Wang, Marco Placenti, Barbara Plank. 824-832 [doi]
• Hasyarasa at SemEval-2020 Task 7: Quantifying Humor as Departure from ExpectednessRavi Theja Desetty, Ranit Chatterjee, Smita Ghaisas. 833-842 [doi]
• JokeMeter at SemEval-2020 Task 7: Convolutional HumorMartin Docekal, Martin Fajcik, Josef Jon, Pavel Smrz. 843-851 [doi]
• KDEhumor at SemEval-2020 Task 7: A Neural Network Model for Detecting Funniness in Dataset HumicroeditRida Miraj, Masaki Aono. 852-857 [doi]
• LRG at SemEval-2020 Task 7: Assessing the Ability of BERT and Derivative Models to Perform Short-Edits Based Humor GradingSiddhant Mahurkar, Rajaswa Patil. 858-864 [doi]
• SSN_NLP at SemEval-2020 Task 7: Detecting Funniness Level Using Traditional Learning with Sentence EmbeddingsKayalvizhi S, D. Thenmozhi, Chandrabose Aravindan. 865-870 [doi]
• YNU-HPCC at SemEval-2020 Task 7: Using an Ensemble BiGRU Model to Evaluate the Humor of Edited News TitlesJoseph Tomasulo, Jin Wang, Xuejie Zhang. 871-875 [doi]
• DSC IIT-ISM at SemEval-2020 Task 8: Bi-Fusion Techniques for Deep Meme Emotion AnalysisPradyumna Gupta, Himanshu Gupta, Aman Sinha. 876-884 [doi]
• IIITG-ADBU at SemEval-2020 Task 8: A Multimodal Approach to Detect Offensive, Sarcastic and Humorous MemesArup Baruah, Kaushik Amar Das, Ferdous A. Barbhuiya, Kuntal Dey. 885-890 [doi]
• NLP_UIOWA at SemEval-2020 Task 8: You're Not the Only One Cursed with Knowledge - Multi Branch Model Memotion AnalysisIngroj Shrestha, Jonathan Rusert. 891-900 [doi]
• NUAA-QMUL at SemEval-2020 Task 8: Utilizing BERT and DenseNet for Internet Meme Emotion AnalysisXiaoyu Guo, Jing Ma, Arkaitz Zubiaga. 901-907 [doi]
• PRHLT-UPV at SemEval-2020 Task 8: Study of Multimodal Techniques for Memes AnalysisGretel Liz De la Peña Sarracén, Paolo Rosso, Anastasia Giachanou. 908-915 [doi]
• YNU-HPCC at SemEval-2020 Task 8: Using a Parallel-Channel Model for Memotion AnalysisLi Yuan, Jin Wang 0008, Xuejie Zhang. 916-921 [doi]
• CS-Embed at SemEval-2020 Task 9: The Effectiveness of Code-switched Word Embeddings for Sentiment AnalysisFrances Adriana Laureano De Leon, Florimond Guéniat, Harish Tayyar Madabushi. 922-927 [doi]
• FII-UAIC at SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text Using CNNLavinia Aparaschivei, Andrei Palihovici, Daniela Gîfu. 928-933 [doi]
• HinglishNLP at SemEval-2020 Task 9: Fine-tuned Language Models for Hinglish Sentiment DetectionMeghana Bhange, Nirant Kasliwal. 934-939 [doi]
• HPCC-YNU at SemEval-2020 Task 9: A Bilingual Vector Gating Mechanism for Sentiment Analysis of Code-Mixed TextJun Kong, Jin Wang, Xuejie Zhang. 940-945 [doi]
• IIITG-ADBU at SemEval-2020 Task 9: SVM for Sentiment Analysis of English-Hindi Code-Mixed TextArup Baruah, Kaushik Amar Das, Ferdous A. Barbhuiya, Kuntal Dey. 946-950 [doi]
• MSR India at SemEval-2020 Task 9: Multilingual Models Can Do Code-Mixing TooAnirudh Srinivasan. 951-956 [doi]
• NLP-CIC at SemEval-2020 Task 9: Analysing Sentiment in Code-switching Language Using a Simple Deep-learning ClassifierJason Angel, Segun Taofeek Aroyehun, Antonio Tamayo, Alexander F. Gelbukh. 957-962 [doi]
• Palomino-Ochoa at SemEval-2020 Task 9: Robust System Based on Transformer for Code-Mixed Sentiment ClassificationDaniel Palomino 0002, José Ochoa Luna. 963-967 [doi]
• ULD@NUIG at SemEval-2020 Task 9: Generative Morphemes with an Attention Model for Sentiment Analysis in Code-Mixed TextKoustava Goswami, Priya Rani, Bharathi Raja Chakravarthi, Theodorus Fransen, John P. McCrae. 968-974 [doi]
• XLP at SemEval-2020 Task 9: Cross-lingual Models with Focal Loss for Sentiment Analysis of Code-Mixing LanguageYili Ma, Liang Zhao, Jie Hao. 975-980 [doi]
• Amobee at SemEval-2020 Task 7: Regularization of Language Model Based ClassifiersAlon Rozental, Dadi Biton, Ido Blank. 981-985 [doi]
• Duluth at SemEval-2020 Task 7: Using Surprise as a Key to Unlock Humorous HeadlinesShuning Jin, Yue Yin, XianE Tang, Ted Pedersen. 986-994 [doi]
• ECNU at SemEval-2020 Task 7: Assessing Humor in Edited News Headlines Using BiLSTM with AttentionTiantian Zhang, Zhixuan Chen, Man Lan. 995-1000 [doi]
• ELMo-NB at SemEval-2020 Task 7: Assessing Sense of Humor in EditedNews Headlines Using ELMo and NBEnas Khwaileh, Muntaha Al-Asa'd. 1001-1007 [doi]
• Ferryman at SemEval-2020 Task 7: Ensemble Model for Assessing Humor in Edited News HeadlinesWeilong Chen, Jipeng Li, Chenghao Huang, Wei Bai, Yanru Zhang, Yan Wang. 1008-1012 [doi]
• Funny3 at SemEval-2020 Task 7: Humor Detection of Edited Headlines with LSTM and TFIDF Neural Network SystemXuefeng Luo, Kuan Tang. 1013-1018 [doi]
• HumorAAC at SemEval-2020 Task 7: Assessing the Funniness of Edited News Headlines through Regression and Trump MentionsAnna-Katharina Dick, Charlotte Weirich, Alla Kutkina. 1019-1025 [doi]
• LMML at SemEval-2020 Task 7: Siamese Transformers for Rating Humor in Edited News HeadlinesPramodith Ballapuram. 1026-1032 [doi]
• LT3 at SemEval-2020 Task 7: Comparing Feature-Based and Transformer-Based Approaches to Detect Funny HeadlinesBram Vanroy, Sofie Labat, Olha Kaminska, Els Lefever, Véronique Hoste. 1033-1040 [doi]
• MLEngineer at SemEval-2020 Task 7: BERT-Flair Based Humor Detection Model (BFHumor)Fara Shatnawi, Malak Abdullah, Mahmoud Hammad. 1041-1048 [doi]
• Smash at SemEval-2020 Task 7: Optimizing the Hyperparameters of ERNIE 2.0 for Humor Ranking and RatingJ. A Meaney, Steven R. Wilson 0001, Walid Magdy. 1049-1054 [doi]
• SO at SemEval-2020 Task 7: DeepPavlov Logistic Regression with BERT Embeddings vs SVR at Funniness EvaluationAnita Soloveva. 1055-1059 [doi]
• UniTuebingenCL at SemEval-2020 Task 7: Humor Detection in News HeadlinesCharlotte Ammer, Lea Grüner. 1060-1065 [doi]
• UTFPR at SemEval-2020 Task 7: Using Co-occurrence Frequencies to Capture UnexpectednessGustavo Henrique Paetzold. 1066-1070 [doi]
• WUY at SemEval-2020 Task 7: Combining BERT and Naive Bayes-SVM for Humor Assessment in Edited News HeadlinesCheng Zhang, Hayato Yamana. 1071-1076 [doi]
• XSYSIGMA at SemEval-2020 Task 7: Method for Predicting Headlines' Humor Based on Auxiliary Sentences with EI-BERTJian Ma, Shu Yi Xie, Meizhi Jin, Lian-Xin Jiang, Yang Mo, Jian-Ping Shen. 1077-1084 [doi]
• BennettNLP at SemEval-2020 Task 8: Multimodal sentiment classification Using Hybrid Hierarchical ClassifierAmbuje Gupta, Harsh Kataria, Souvik Mishra, Tapas Badal, Vipul Mishra. 1085-1093 [doi]
• BERT at SemEval-2020 Task 8: Using BERT to Analyse Meme EmotionsAdithya Avvaru, Sanath Vobilisetty. 1094-1099 [doi]
• CN-HIT-MI.T at SemEval-2020 Task 8: Memotion Analysis Based on BERTZhen Li, Yaojie Zhang, Bing Xu, Tiejun Zhao. 1100-1105 [doi]
• CSECU_KDE_MA at SemEval-2020 Task 8: A Neural Attention Model for Memotion AnalysisAbu Nowshed Chy, Umme Aymun Siddiqua, Masaki Aono. 1106-1111 [doi]
• Gundapusunil at SemEval-2020 Task 8: Multimodal Memotion AnalysisSunil Gundapu, Radhika Mamidi. 1112-1119 [doi]
• Guoym at SemEval-2020 Task 8: Ensemble-based Classification of Visuo-Lingual Metaphor in MemesYingmei Guo, Jinfa Huang, Yanlong Dong, Mingxing Xu. 1120-1125 [doi]
• Hitachi at SemEval-2020 Task 8: Simple but Effective Modality Ensemble for Meme Emotion RecognitionTerufumi Morishita, Gaku Morio, Shota Horiguchi, Hiroaki Ozaki, Toshinori Miyoshi. 1126-1134 [doi]
• IITK at SemEval-2020 Task 8: Unimodal and Bimodal Sentiment Analysis of Internet MemesVishal Keswani, Sakshi Singh, Suryansh Agarwal, Ashutosh Modi. 1135-1140 [doi]
• Infotec + CentroGEO at SemEval-2020 Task 8: Deep Learning and Text Categorization approach for Memes classificationGuillermo Ruiz, Eric Sadit Tellez, Daniela Moctezuma, Sabino Miranda-Jiménez, Tania A. Ramirez-delReal, Mario Graff. 1141-1147 [doi]
• KAFK at SemEval-2020 Task 8: Extracting Features from Pre-trained Neural Networks to Classify Internet MemesKaushik Amar Das, Arup Baruah, Ferdous Ahmed Barbhuiya, Kuntal Dey. 1148-1154 [doi]
• LT3 at SemEval-2020 Task 8: Multi-Modal Multi-Task Learning for Memotion AnalysisPranaydeep Singh, Nina Bauwelinck, Els Lefever. 1155-1162 [doi]
• Memebusters at SemEval-2020 Task 8: Feature Fusion Model for Sentiment Analysis on Memes Using Transfer LearningMayukh Sharma, Ilanthenral Kandasamy, W. B. Vasantha. 1163-1171 [doi]
• MemoSYS at SemEval-2020 Task 8: Multimodal Emotion Analysis in MemesIrina Bejan. 1172-1178 [doi]
• NIT-Agartala-NLP-Team at SemEval-2020 Task 8: Building Multimodal Classifiers to Tackle Internet HumorSteve Durairaj Swamy, Shubham Laddha, Basil Abdussalam, Debayan Datta, Anupam Jamatia. 1179-1189 [doi]
• SIS@IIITH at SemEval-2020 Task 8: An Overview of Simple Text Classification Methods for Meme AnalysisSravani Boinepelli, Manish Shrivastava 0001, Vasudeva Varma. 1190-1194 [doi]
• UI at SemEval-2020 Task 8: Text-Image Fusion for Sentiment ClassificationAndi Suciati, Indra Budi. 1195-1200 [doi]
• UoR at SemEval-2020 Task 8: Gaussian Mixture Modelling (GMM) Based Sampling Approach for Multi-modal Memotion AnalysisZehao Liu, Emmanuel Osei-Brefo, Siyuan Chen, Huizhi Liang. 1201-1207 [doi]
• UPB at SemEval-2020 Task 8: Joint Textual and Visual Modeling in a Multi-Task Learning Architecture for Memotion AnalysisGeorge-Alexandru Vlad, George-Eduard Zaharia, Dumitru-Clementin Cercel, Costin-Gabriel Chiru, Stefan Trausan-Matu. 1208-1214 [doi]
• Urszula Wali'nska at SemEval-2020 Task 8: Fusion of Text and Image Features Using LSTM and VGG16 for Memotion AnalysisUrszula Walinska, Jedrzej Potoniec. 1215-1220 [doi]
• BAKSA at SemEval-2020 Task 9: Bolstering CNN with Self-Attention for Sentiment Analysis of Code Mixed TextAyush Kumar, Harsh Agarwal, Keshav Bansal, Ashutosh Modi. 1221-1226 [doi]
• C1 at SemEval-2020 Task 9: SentiMix: Sentiment Analysis for Code-Mixed Social Media Text Using Feature EngineeringLaksh Advani, Clement Lu, Suraj Maharjan. 1227-1232 [doi]
• Deep Learning Brasil - NLP at SemEval-2020 Task 9: Sentiment Analysis of Code-Mixed Tweets Using Ensemble of Language ModelsManoel Veríssimo dos Santos Neto, Ayrton Denner da Silva Amaral, Nádia Félix F. da Silva, Anderson da Silva Soares. 1233-1238 [doi]
• FiSSA at SemEval-2020 Task 9: Fine-tuned for FeelingsBertelt Braaksma, Richard Scholtens, Stan van Suijlekom, Remy Wang, Ahmet Üstün. 1239-1246 [doi]
• Gundapusunil at SemEval-2020 Task 9: Syntactic Semantic LSTM Architecture for SENTIment Analysis of Code-MIXed DataSunil Gundapu, Radhika Mamidi. 1247-1252 [doi]
• HCMS at SemEval-2020 Task 9: A Neural Approach to Sentiment Analysis for Code-Mixed TextsAditya Srivastava, V. Harsha Vardhan. 1253-1258 [doi]
• IIT Gandhinagar at SemEval-2020 Task 9: Code-Mixed Sentiment Classification Using Candidate Sentence Generation and SelectionVivek Srivastava, Mayank Singh 0001. 1259-1264 [doi]
• IRLab_DAIICT at SemEval-2020 Task 9: Machine Learning and Deep Learning Methods for Sentiment Analysis of Code-Mixed TweetsApurva Parikh, Abhimanyu Singh Bisht, Prasenjit Majumder. 1265-1269 [doi]
• IUST at SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text Using Deep Neural Networks and Linear BaselinesSoroush Javdan, Taha Shangipour Ataei, Behrouz Minaei-Bidgoli. 1270-1275 [doi]
• JUNLP at SemEval-2020 Task 9: Sentiment Analysis of Hindi-English Code Mixed Data Using Grid Search Cross ValidationAvishek Garain, Sainik Kumar Mahata, Dipankar Das 0001. 1276-1280 [doi]
• LIMSI_UPV at SemEval-2020 Task 9: Recurrent Convolutional Neural Network for Code-mixed Sentiment AnalysisSomnath Banerjee, Sahar Ghannay, Sophie Rosset, Anne Vilnat, Paolo Rosso. 1281-1287 [doi]
• LT3 at SemEval-2020 Task 9: Cross-lingual Embeddings for Sentiment Analysis of Hinglish Social Media TextPranaydeep Singh, Els Lefever. 1288-1293 [doi]
• MeisterMorxrc at SemEval-2020 Task 9: Fine-Tune Bert and Multitask Learning for Sentiment Analysis of Code-Mixed TweetsQi Wu, Peng Wang, Chenghao Huang. 1294-1297 [doi]
• NITS-Hinglish-SentiMix at SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text Using an Ensemble ModelSubhra Jyoti Baroi, Nivedita Singh, Ringki Das, Thoudam Doren Singh. 1298-1303 [doi]
• Reed at SemEval-2020 Task 9: Fine-Tuning and Bag-of-Words Approaches to Code-Mixed Sentiment AnalysisVinay Gopalan, Mark Hopkins. 1304-1309 [doi]
• Team_Swift at SemEval-2020 Task 9: Tiny Data Specialists through Domain-Specific Pre-training on Code-Mixed DataAditya Malte, Pratik Bhavsar, Sushant Rathi. 1310-1315 [doi]
• TueMix at SemEval-2020 Task 9: Logistic Regression with Linguistic Feature SetElizabeth Bear, Diana Constantina Hoefels, Mihai Manolescu. 1316-1321 [doi]
• UPB at SemEval-2020 Task 9: Identifying Sentiment in Code-Mixed Social Media Texts Using Transformers and Multi-Task LearningGeorge-Eduard Zaharia, George-Alexandru Vlad, Dumitru-Clementin Cercel, Traian Rebedea, Costin-Gabriel Chiru. 1322-1330 [doi]
• Voice@SRIB at SemEval-2020 Tasks 9 and 12: Stacked Ensemblingmethod for Sentiment and Offensiveness detection in Social MediaAbhishek Singh, Surya Pratap Singh Parmar. 1331-1341 [doi]
• WESSA at SemEval-2020 Task 9: Code-Mixed Sentiment Analysis Using TransformersAhmed Sultan, Mahmoud Salim, Amina Gaber, Islam El Hosary. 1342-1347 [doi]
• Will_go at SemEval-2020 Task 9: An Accurate Approach for Sentiment Analysis on Hindi-English Tweets Based on Bert and Pesudo Label StrategyWei Bao, Weilong Chen, Wei Bai, Yan Zhuang, Mingyuan Cheng, Xiangyu Ma. 1348-1353 [doi]
• Zyy1510 Team at SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text with Sub-word Level RepresentationsYueying Zhu, Xiaobing Zhou, Hongling Li, Kunjie Dong. 1354-1359 [doi]
• SemEval-2020 Task 10: Emphasis Selection for Written Text in Visual MediaAmirreza Shirani, Franck Dernoncourt, Nedim Lipka, Paul Asente, Jose Echevarria, Thamar Solorio. 1360-1370 [doi]
• IDS at SemEval-2020 Task 10: Does Pre-trained Language Model Know What to Emphasize?Jaeyoul Shin, Taeuk Kim, Sang-goo Lee. 1371-1376 [doi]
• SemEval-2020 Task 11: Detection of Propaganda Techniques in News ArticlesGiovanni Da San Martino, Alberto Barrón-Cedeño, Henning Wachsmuth, Rostislav Petrov, Preslav Nakov. 1377-1414 [doi]
• ApplicaAI at SemEval-2020 Task 11: On RoBERTa-CRF, Span CLS and Whether Self-Training Helps ThemDawid Jurkiewicz, Lukasz Borchmann, Izabela Kosmala, Filip Gralinski. 1415-1424 [doi]
• SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)Marcos Zampieri, Preslav Nakov, Sara Rosenthal, Pepa Atanasova, Georgi Karadzhov, Hamdy Mubarak, Leon Derczynski, Zeses Pitenis, Çagri Çöltekin. 1425-1447 [doi]
• Galileo at SemEval-2020 Task 12: Multi-lingual Learning for Offensive Language Identification Using Pre-trained Language ModelsShuohuan Wang, Jiaxiang Liu 0004, Xuan Ouyang, Yu Sun. 1448-1455 [doi]
• ERNIE at SemEval-2020 Task 10: Learning Word Emphasis Selection by Pre-trained Language ModelZhengjie Huang, Shikun Feng, Weiyue Su, Xuyi Chen, Shuohuan Wang, Jiaxiang Liu 0004, Xuan Ouyang, Yu Sun. 1456-1461 [doi]
• Aschern at SemEval-2020 Task 11: It Takes Three to Tango: RoBERTa, CRF, and Transfer LearningAnton Chernyavskiy, Dmitry Ilvovsky, Preslav Nakov. 1462-1468 [doi]
• CyberWallE at SemEval-2020 Task 11: An Analysis of Feature Engineering for Ensemble Models for Propaganda DetectionVerena Blaschke, Maxim Korniyenko, Sam Tureski. 1469-1480 [doi]
• Inno at SemEval-2020 Task 11: Leveraging Pure Transfomer for Multi-Class Propaganda DetectionDmitry Grigorev, Vladimir Ivanov. 1481-1487 [doi]
• NoPropaganda at SemEval-2020 Task 11: A Borrowed Approach to Sequence Tagging and Text ClassificationIlya Dimov, Vladislav Korzun, Ivan Smurov. 1488-1494 [doi]
• NTUAAILS at SemEval-2020 Task 11: Propaganda Detection and Classification with biLSTMs and ELMoAnastasios Arsenos, Georgios Siolas. 1495-1501 [doi]
• Team DoNotDistribute at SemEval-2020 Task 11: Features, Finetuning, and Data Augmentation in Neural Models for Propaganda Detection in News ArticlesMichael Kranzlein, Shabnam Behzad, Nazli Goharian. 1502-1508 [doi]
• YNU-HPCC at SemEval-2020 Task 11: LSTM Network for Detection of Propaganda Techniques in News ArticlesJiaxu Dao, Jin Wang, Xuejie Zhang. 1509-1515 [doi]
• AdelaideCyC at SemEval-2020 Task 12: Ensemble of Classifiers for Offensive Language Detection in Social MediaMahen Herath, Thushari Atapattu, Hoang Anh Dung, Christoph Treude, Katrina Falkner. 1516-1523 [doi]
• ANDES at SemEval-2020 Task 12: A Jointly-trained BERT Multilingual Model for Offensive Language DetectionJuan Manuel Pérez, Aymé Arango, Franco M. Luque. 1524-1531 [doi]
• BhamNLP at SemEval-2020 Task 12: An Ensemble of Different Word Embeddings and Emotion Transfer Learning for Arabic Offensive Language Identification in Social MediaAbdullah I. Alharbi, Mark Lee. 1532-1538 [doi]
• FBK-DH at SemEval-2020 Task 12: Using Multi-channel BERT for Multilingual Offensive Language DetectionCamilla Casula, Alessio Palmero Aprosio, Stefano Menini, Sara Tonelli. 1539-1545 [doi]
• GruPaTo at SemEval-2020 Task 12: Retraining mBERT on Social Media and Fine-tuned Offensive Language ModelsDavide Colla, Tommaso Caselli, Valerio Basile, Jelena Mitrovic, Michael Granitzer. 1546-1554 [doi]
• GUIR at SemEval-2020 Task 12: Domain-Tuned Contextualized Models for Offensive Language DetectionSajad Sotudeh, Tong Xiang, Hao-Ren Yao, Sean MacAvaney, Eugene Yang, Nazli Goharian, Ophir Frieder. 1555-1561 [doi]
• IIITG-ADBU at SemEval-2020 Task 12: Comparison of BERT and BiLSTM in Detecting Offensive LanguageArup Baruah, Kaushik Amar Das, Ferdous A. Barbhuiya, Kuntal Dey. 1562-1568 [doi]
• LT@Helsinki at SemEval-2020 Task 12: Multilingual or Language-specific BERT?Marc Pàmies, Emily Öhman, Kaisla Kajava, Jörg Tiedemann. 1569-1575 [doi]
• NLPDove at SemEval-2020 Task 12: Improving Offensive Language Detection with Cross-lingual TransferHwijeen Ahn, Jimin Sun, Chan Young Park, Jungyun Seo. 1576-1586 [doi]
• Nova-Wang at SemEval-2020 Task 12: OffensEmblert: An Ensemble ofOffensive Language ClassifiersSusan Wang, Zita Marinho. 1587-1597 [doi]
• NUIG at SemEval-2020 Task 12: Pseudo Labelling for Offensive Content ClassificationShardul Suryawanshi, Mihael Arcan, Paul Buitelaar. 1598-1604 [doi]
• PRHLT-UPV at SemEval-2020 Task 12: BERT for Multilingual Offensive Language DetectionGretel Liz De la Peña Sarracén, Paolo Rosso. 1605-1614 [doi]
• PUM at SemEval-2020 Task 12: Aggregation of Transformer-based Models' Features for Offensive Language RecognitionPiotr Janiszewski, Mateusz Skiba, Urszula Walinska. 1615-1621 [doi]
• SINAI at SemEval-2020 Task 12: Offensive Language Identification Exploring Transfer Learning ModelsFlor Miriam Plaza del Arco, M. Dolores Molina-González, Luis Alfonso Ureña López, Maite Martín-Valdivia. 1622-1627 [doi]
• Team Oulu at SemEval-2020 Task 12: Multilingual Identification of Offensive Language, Type and Target of Twitter Post Using Translated DatasetsMd Saroar Jahan. 1628-1637 [doi]
• UHH-LT at SemEval-2020 Task 12: Fine-Tuning of Pre-Trained Transformer Networks for Offensive Language DetectionGregor Wiedemann, Seid Muhie Yimam, Chris Biemann. 1638-1644 [doi]
• EL-BERT at SemEval-2020 Task 10: A Multi-Embedding Ensemble Based Approach for Emphasis Selection in Visual MediaChandresh S. Kanani, Sriparna Saha 0001, Pushpak Bhattacharyya. 1645-1651 [doi]
• FPAI at SemEval-2020 Task 10: A Query Enhanced Model with RoBERTa for Emphasis SelectionChenyang Guo, Xiaolong Hou, Junsong Ren, Lian-Xin Jiang, Yang Mo, Haiqin Yang, Jian-Ping Shen. 1652-1657 [doi]
• Hitachi at SemEval-2020 Task 10: Emphasis Distribution Fusion on Fine-Tuned Language ModelsGaku Morio, Terufumi Morishita, Hiroaki Ozaki, Toshinori Miyoshi. 1658-1664 [doi]
• IITK at SemEval-2020 Task 10: Transformers for Emphasis SelectionVipul Singhal, Sahil Dhull, Rishabh Agarwal, Ashutosh Modi. 1665-1670 [doi]
• LAST at SemEval-2020 Task 10: Finding Tokens to Emphasise in Short Written Texts with Precomputed Embedding Models and LightGBMYves Bestgen. 1671-1677 [doi]
• MIDAS at SemEval-2020 Task 10: Emphasis Selection Using Label Distribution Learning and Contextual EmbeddingsSarthak Anand, Pradyumna Gupta, Hemant Yadav, Debanjan Mahata, Rakesh Gosangi, Haimin Zhang, Rajiv Ratn Shah. 1678-1684 [doi]
• Randomseed19 at SemEval-2020 Task 10: Emphasis Selection for Written Text in Visual MediaAleksandr Shatilov, Denis Gordeev, Alexey Rey. 1685-1690 [doi]
• TextLearner at SemEval-2020 Task 10: A Contextualized Ranking System in Solving Emphasis Selection in TextZhishen Yang, Lars Wolfsteller, Naoaki Okazaki. 1691-1697 [doi]
• TëXtmarkers at SemEval-2020 Task 10: Emphasis Selection with Agreement Dependent Crowd LayersKevin Glocker, Stefanos Andreas Markianos Wright. 1698-1703 [doi]
• UIC-NLP at SemEval-2020 Task 10: Exploring an Alternate Perspective on EvaluationPhilip Hossu, Natalie Parde. 1704-1709 [doi]
• YNU-HPCC at SemEval-2020 Task 10: Using a Multi-granularity Ordinal Classification of the BiLSTM Model for Emphasis SelectionDawei Liao, Jin Wang 0008, Xuejie Zhang. 1710-1715 [doi]
• 3218IR at SemEval-2020 Task 11: Conv1D and Word Embedding in Propaganda Span Identification at News ArticlesDimas Sony Dewantara, Indra Budi, Muhammad Okky Ibrohim. 1716-1721 [doi]
• BPGC at SemEval-2020 Task 11: Propaganda Detection in News Articles with Multi-Granularity Knowledge Sharing and Linguistic Features Based Ensemble LearningRajaswa Patil, Somesh Singh 0002, Swati Agarwal 0001. 1722-1731 [doi]
• DUTH at SemEval-2020 Task 11: BERT with Entity Mapping for Propaganda ClassificationAnastasios Bairaktaris, Symeon Symeonidis, Avi Arampatzis. 1732-1738 [doi]
• Hitachi at SemEval-2020 Task 11: An Empirical Study of Pre-Trained Transformer Family for Propaganda DetectionGaku Morio, Terufumi Morishita, Hiroaki Ozaki, Toshinori Miyoshi. 1739-1748 [doi]
• JUST at SemEval-2020 Task 11: Detecting Propaganda Techniques Using BERT Pre-trained ModelOla Altiti, Malak Abdullah, Rasha Obiedat. 1749-1755 [doi]
• LTIatCMU at SemEval-2020 Task 11: Incorporating Multi-Level Features for Multi-Granular Propaganda Span IdentificationSopan Khosla, Rishabh Joshi, Ritam Dutt, Alan W. Black, Yulia Tsvetkov. 1756-1763 [doi]
• newsSweeper at SemEval-2020 Task 11: Context-Aware Rich Feature Representations for Propaganda ClassificationParamansh Singh, Siraj Sandhu, Subham Kumar, Ashutosh Modi. 1764-1770 [doi]
• NLFIIT at SemEval-2020 Task 11: Neural Network Architectures for Detection of Propaganda Techniques in News ArticlesMatej Martinkovic, Samuel Pecar, Marián Simko. 1771-1778 [doi]
• PsuedoProp at SemEval-2020 Task 11: Propaganda Span Detection Using BERT-CRF and Ensemble Sentence Level ClassifierAniruddha Chauhan, Harshita Diddee. 1779-1785 [doi]
• SkoltechNLP at SemEval-2020 Task 11: Exploring Unsupervised Text Augmentation for Propaganda DetectionDaryna Dementieva, Igor Markov, Alexander Panchenko. 1786-1792 [doi]
• SocCogCom at SemEval-2020 Task 11: Characterizing and Detecting Propaganda Using Sentence-Level Emotional Salience FeaturesGangeshwar Krishnamurthy, Raj Kumar Gupta, Yinping Yang. 1793-1801 [doi]
• Solomon at SemEval-2020 Task 11: Ensemble Architecture for Fine-Tuned Propaganda Detection in News ArticlesMayank Raj, Ajay Jaiswal, Rohit R. R, Ankita Gupta, Sudeep Kumar Sahoo, Vertika Srivastava, Yeon Hyang Kim. 1802-1807 [doi]
• syrapropa at SemEval-2020 Task 11: BERT-based Models Design for Propagandistic Technique and Span DetectionJinfen Li, Lu Xiao. 1808-1816 [doi]
• Team DiSaster at SemEval-2020 Task 11: Combining BERT and Hand-crafted Features for Identifying Propaganda Techniques in NewsAnders Kaas, Viktor Torp Thomsen, Barbara Plank. 1817-1822 [doi]
• Transformers at SemEval-2020 Task 11: Propaganda Fragment Detection Using Diversified BERT Architectures Based Ensemble LearningEkansh Verma, Vinodh Motupalli, Souradip Chakraborty. 1823-1828 [doi]
• TTUI at SemEval-2020 Task 11: Propaganda Detection with Transfer Learning and EnsemblesMoonsung Kim, Steven Bethard. 1829-1834 [doi]
• UAIC1860 at SemEval-2020 Task 11: Detection of Propaganda Techniques in News ArticlesVlad Ermurachi, Daniela Gîfu. 1835-1840 [doi]
• UMSIForeseer at SemEval-2020 Task 11: Propaganda Detection by Fine-Tuning BERT with Resampling and Ensemble LearningYunzhe Jiang, Cristina Garbacea, Qiaozhu Mei. 1841-1846 [doi]
• UNTLing at SemEval-2020 Task 11: Detection of Propaganda Techniques in English News ArticlesMaia Petee, Alexis Palmer. 1847-1852 [doi]
• UPB at SemEval-2020 Task 11: Propaganda Detection with Domain-Specific Trained BERTAndrei Paraschiv, Dumitru-Clementin Cercel, Mihai Dascalu. 1853-1857 [doi]
• UTMN at SemEval-2020 Task 11: A Kitchen Solution to Automatic Propaganda DetectionElena Mikhalkova, Nadezhda Ganzherli, Anna Glazkova, Yuliya Bidulya. 1858-1864 [doi]
• WMD at SemEval-2020 Tasks 7 and 11: Assessing Humor and Propaganda Using Unsupervised Data AugmentationGuillaume Daval-Frerot, Yannick Weis. 1865-1874 [doi]
• YNUtaoxin at SemEval-2020 Task 11: Identification Fragments of Propaganda Technique by Neural Sequence Labeling Models with Different Tagging Schemes and Pre-trained Language ModelXin Tao, Xiaobing Zhou. 1875-1880 [doi]
• AlexU-BackTranslation-TL at SemEval-2020 Task 12: Improving Offensive Language Detection Using Data Augmentation and Transfer LearningMai Ibrahim, Marwan Torki, Nagwa M. El-Makky. 1881-1890 [doi]
• ALT at SemEval-2020 Task 12: Arabic and English Offensive Language Identification in Social MediaSabit Hassan, Younes Samih, Hamdy Mubarak, Ahmed Abdelali. 1891-1897 [doi]
• Amsqr at SemEval-2020 Task 12: Offensive Language Detection Using Neural Networks and Anti-adversarial FeaturesAlejandro Mosquera. 1898-1905 [doi]
• BRUMS at SemEval-2020 Task 12: Transformer Based Multilingual Offensive Language Identification in Social MediaTharindu Ranasinghe, Hansi Hettiarachchi. 1906-1915 [doi]
• CoLi at UdS at SemEval-2020 Task 12: Offensive Tweet Detection with EnsemblingKathryn Chapman, Johannes Bernhard, Dietrich Klakow. 1916-1924 [doi]
• CyberTronics at SemEval-2020 Task 12: Multilingual Offensive Language Identification over Social MediaSayanta Paul, Sriparna Saha 0001, Mohammed Hasanuzzaman. 1925-1931 [doi]
• DoTheMath at SemEval-2020 Task 12 : Deep Neural Networks with Self Attention for Arabic Offensive Language DetectionZoher Orabe, Bushr Haddad, Nada Ghneim, Anas Al-Abood. 1932-1937 [doi]
• Duluth at SemEval-2020 Task 12: Offensive Tweet Identification in English with Logistic RegressionTed Pedersen. 1938-1946 [doi]
• Ferryman at SemEval-2020 Task 12: BERT-Based Model with Advanced Improvement Methods for Multilingual Offensive Language IdentificationWeilong Chen, Peng Wang, Jipeng Li, Yuanshuai Zheng, Yan Wang, Yanru Zhang. 1947-1952 [doi]
• Garain at SemEval-2020 Task 12: Sequence Based Deep Learning for Categorizing Offensive Language in Social MediaAvishek Garain. 1953-1960 [doi]
• Hitachi at SemEval-2020 Task 12: Offensive Language Identification with Noisy Labels Using Statistical Sampling and Post-ProcessingManikandan Ravikiran, Amin Ekant Muljibhai, Toshinori Miyoshi, Hiroaki Ozaki, Yuta Koreeda, Sakata Masayuki. 1961-1967 [doi]
• I2C at SemEval-2020 Task 12: Simple but Effective Approaches to Offensive Speech Detection in TwitterVictoria Pachón Álvarez, Jacinto Mata Vázquez, José Manuel López Betanzos, José Luis Arjona Fernández. 1968-1977 [doi]
• iCompass at SemEval-2020 Task 12: From a Syntax-ignorant N-gram Embeddings Model to a Deep Bidirectional Language ModelAbir Messaoudi, Hatem Haddad, Moez Ben Haj Hmida. 1978-1982 [doi]
• IITP-AINLPML at SemEval-2020 Task 12: Offensive Tweet Identification and Target Categorization in a Multitask EnvironmentSoumitra Ghosh, Asif Ekbal, Pushpak Bhattacharyya. 1983-1991 [doi]
• INGEOTEC at SemEval-2020 Task 12: Multilingual Classification of Offensive TextSabino Miranda-Jiménez, Eric Sadit Tellez, Mario Graff, Daniela Moctezuma. 1992-1997 [doi]
• IR3218-UI at SemEval-2020 Task 12: Emoji Effects on Offensive Language IdentifiCationSandy Kurniawan, Indra Budi, Muhammad Okky Ibrohim. 1998-2005 [doi]
• IRLab_DAIICT at SemEval-2020 Task 12: Machine Learning and Deep Learning Methods for Offensive Language IdentificationApurva Parikh, Abhimanyu Singh Bisht, Prasenjit Majumder. 2006-2011 [doi]
• IRlab@IITV at SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media Using SVMAnita Saroj, Supriya Chanda, Sukomal Pal. 2012-2016 [doi]
• JCT at SemEval-2020 Task 12: Offensive Language Detection in Tweets Using Preprocessing Methods, Character and Word N-gramsMoshe Uzan, Yaakov HaCohen-Kerner. 2017-2022 [doi]
• KAFK at SemEval-2020 Task 12: Checkpoint Ensemble of Transformers for Hate Speech ClassificationKaushik Amar Das, Arup Baruah, Ferdous Ahmed Barbhuiya, Kuntal Dey. 2023-2029 [doi]
• KDELAB at SemEval-2020 Task 12: A System for Estimating Aggression of Tweets Using Two Layers of BERT FeaturesKeisuke Hanahata, Masaki Aono. 2030-2034 [doi]
• KEIS@JUST at SemEval-2020 Task 12: Identifying Multilingual Offensive Tweets Using Weighted Ensemble and Fine-Tuned BERTSaia Khaled Tawalbeh, Mahmoud Hammad, Mohammad Al-Smadi. 2035-2044 [doi]
• KS@LTH at SemEval-2020 Task 12: Fine-tuning Multi- and Monolingual Transformer Models for Offensive Language DetectionKasper Socha. 2045-2053 [doi]
• KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social MediaAli Safaya, Moutasem Abdullatif, Deniz Yuret. 2054-2059 [doi]
• Kungfupanda at SemEval-2020 Task 12: BERT-Based Multi-TaskLearning for Offensive Language DetectionWenliang Dai, Tiezheng Yu, Zihan Liu, Pascale Fung. 2060-2066 [doi]
• Lee at SemEval-2020 Task 12: A BERT Model Based on the Maximum Self-ensemble Strategy for Identifying Offensive LanguageJunyi Li, Xiaobing Zhou, Zichen Zhang. 2067-2072 [doi]
• LIIR at SemEval-2020 Task 12: A Cross-Lingual Augmentation Approach for Multilingual Offensive Language IdentificationErfan Ghadery, Marie-Francine Moens. 2073-2079 [doi]
• LISAC FSDM-USMBA Team at SemEval-2020 Task 12: Overcoming AraBERT's pretrain-finetune discrepancy for Arabic offensive language identificationHamza Alami, Said Ouatik El Alaoui, Abdessamad Benlahbib, Noureddine Ennahnahi. 2080-2085 [doi]
• NAYEL at SemEval-2020 Task 12: TF/IDF-Based Approach for Automatic Offensive Language Detection in Arabic TweetsHamada A. Nayel. 2086-2089 [doi]
• NLP_Passau at SemEval-2020 Task 12: Multilingual Neural Network for Offensive Language Detection in English, Danish and TurkishOmar Hussein, Hachem Sfar, Jelena Mitrovic, Michael Granitzer. 2090-2097 [doi]
• nlpUP at SemEval-2020 Task 12 : A Blazing Fast System for Offensive Language DetectionEhab Hamdy, Jelena Mitrovic, Michael Granitzer. 2098-2104 [doi]
• NTU_NLP at SemEval-2020 Task 12: Identifying Offensive Tweets Using Hierarchical Multi-Task Learning ApproachPo-Chun Chen, Hen-Hsen Huang, Hsin-Hsi Chen. 2105-2110 [doi]
• PGSG at SemEval-2020 Task 12: BERT-LSTM with Tweets' Pretrained Model and Noisy Student Training MethodBao-Tran Pham-Hong, Setu Chokshi. 2111-2116 [doi]
• Pin_cod_ at SemEval-2020 Task 12: Injecting Lexicons into Bidirectional Long Short-Term Memory Networks to Detect Turkish Offensive TweetsPinar Arslan. 2117-2122 [doi]
• problemConquero at SemEval-2020 Task 12: Transformer and Soft Label-based ApproachesKarishma Laud, Jagriti Singh, Randeep Kumar Sahu, Ashutosh Modi. 2123-2132 [doi]
• SalamNET at SemEval-2020 Task 12: Deep Learning Approach for Arabic Offensive Language DetectionFatemah Husain, Jooyeon Lee, Sam Henry 0001, Özlem Uzuner. 2133-2139 [doi]
• Smatgrisene at SemEval-2020 Task 12: Offense Detection by AI - with a Pinch of Real IPeter Juel Henrichsen, Marianne Rathje. 2140-2145 [doi]
• Sonal.kumari at SemEval-2020 Task 12: Social Media Multilingual Offensive Text Identification and Categorization Using Neural Network ModelsSonal Kumari. 2146-2154 [doi]
• Ssn_nlp at SemEval 2020 Task 12: Offense Target Identification in Social Media Using Traditional and Deep Machine Learning ApproachesThenmozhi D, Nandhinee P. R, Arunima S., Amlan Sengupta. 2155-2160 [doi]
• SSN_NLP_MLRG at SemEval-2020 Task 12: Offensive Language Identification in English, Danish, Greek Using BERT and Machine Learning ApproachThenmozhi D, A. Kalaivani. 2161-2170 [doi]
• SU-NLP at SemEval-2020 Task 12: Offensive Language IdentifiCation in Turkish TweetsAnil Özdemir, Reyyan Yeniterzi. 2171-2176 [doi]
• TAC at SemEval-2020 Task 12: Ensembling Approach for Multilingual Offensive Language Identification in Social MediaTalha Anwar, Omer Baig. 2177-2182 [doi]
• Team Rouges at SemEval-2020 Task 12: Cross-lingual Inductive Transfer to Detect Offensive LanguageTanvi Dadu, Kartikey Pant. 2183-2189 [doi]
• TECHSSN at SemEval-2020 Task 12: Offensive Language Detection Using BERT EmbeddingsRajalakshmi Sivanaiah, Angel Suseelan, S. Milton Rajendram, T. T. Mirnalinee. 2190-2196 [doi]
• TheNorth at SemEval-2020 Task 12: Hate Speech Detection Using RoBERTaPedro Alonso, Rajkumar Saini, György Kovács. 2197-2202 [doi]
• UJNLP at SemEval-2020 Task 12: Detecting Offensive Language Using Bidirectional TransformersYinnan Yao, Nan Su, Kun Ma. 2203-2208 [doi]
• UNT Linguistics at SemEval-2020 Task 12: Linear SVC with Pre-trained Word Embeddings as Document Vectors and Targeted Linguistic FeaturesJared Fromknecht, Alexis Palmer. 2209-2215 [doi]
• UoB at SemEval-2020 Task 12: Boosting BERT with Corpus Level InformationWah Meng Lim, Harish Tayyar Madabushi. 2216-2221 [doi]
• UPB at SemEval-2020 Task 12: Multilingual Offensive Language Detection on Social Media by Fine-tuning a Variety of BERT-based ModelsMircea-Adrian Tanase, Dumitru-Clementin Cercel, Costin-Gabriel Chiru. 2222-2231 [doi]
• UTFPR at SemEval 2020 Task 12: Identifying Offensive Tweets with Lightweight EnsemblesMarcos Aurélio Hermogenes Boriola, Gustavo Henrique Paetzold. 2232-2236 [doi]
• WOLI at SemEval-2020 Task 12: Arabic Offensive Language Identification on Different Twitter DatasetsYasser Otiefy, Ahmed Abdelmalek, Islam El Hosary. 2237-2243 [doi]
• XD at SemEval-2020 Task 12: Ensemble Approach to Offensive Language Identification in Social Media Using Transformer EncodersXiangjue Dong, Jinho D. Choi. 2244-2250 [doi]
• YNU_oxz at SemEval-2020 Task 12: Bidirectional GRU with Capsule for Identifying Multilingual Offensive LanguageXiaozhi Ou, Hongling Li. 2251-2257 [doi]