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ORCID14th SemEval@COLING 2020: Barcelona (online)
- Aurélie Herbelot, Xiaodan Zhu, Alexis Palmer, Nathan Schneider, Jonathan May, Ekaterina Shutova:
Proceedings of the Fourteenth Workshop on Semantic Evaluation, SemEval@COLING 2020, Barcelona (online), December 12-13, 2020. International Committee for Computational Linguistics 2020, ISBN 978-1-952148-31-6 - Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen
, Haim Dubossarsky, Nina Tahmasebi:
SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection. 1-23 - Goran Glavas, Ivan Vulic, Anna Korhonen, Simone Paolo Ponzetto:
SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment. 24-35 - Carlos Santos Armendariz, Matthew Purver, Senja Pollak, Nikola Ljubesic, Matej Ulcar, Ivan Vulic, Mohammad Taher Pilehvar:
SemEval-2020 Task 3: Graded Word Similarity in Context. 36-49 - Christin Beck:
DiaSense at SemEval-2020 Task 1: Modeling Sense Change via Pre-trained BERT Embeddings. 50-58 - Lucas Rafael Costella Pessutto, Tiago de Melo, Viviane P. Moreira, Altigran S. da Silva:
BabelEnconding at SemEval-2020 Task 3: Contextual Similarity as a Combination of Multilingualism and Language Models. 59-66 - Matej Martinc, Syrielle Montariol, Elaine Zosa, Lidia Pivovarova:
Discovery Team at SemEval-2020 Task 1: Context-sensitive Embeddings Not Always Better than Static for Semantic Change Detection. 67-73 - Pierluigi Cassotti, Annalina Caputo, Marco Polignano, Pierpaolo Basile:
GM-CTSC at SemEval-2020 Task 1: Gaussian Mixtures Cross Temporal Similarity Clustering. 74-80 - Jens Kaiser, Dominik Schlechtweg, Sean Papay, Sabine Schulte im Walde:
IMS at SemEval-2020 Task 1: How Low Can You Go? Dimensionality in Lexical Semantic Change Detection. 81-89 - Efrat Amar, Chaya Liebeskind:
JCT at SemEval-2020 Task 1: Combined Semantic Vector Spaces Models for Unsupervised Lexical Semantic Change Detection. 90-97 - Ran Iwamoto, Masahiro Yukawa:
RIJP at SemEval-2020 Task 1: Gaussian-based Embeddings for Semantic Change Detection. 98-104 - Maurício Gruppi, Sibel Adali, Pin-Yu Chen:
SChME at SemEval-2020 Task 1: A Model Ensemble for Detecting Lexical Semantic Change. 105-111 - Amaru Cuba Gyllensten, Evangelia Gogoulou, Ariel Ekgren, Magnus Sahlgren:
SenseCluster at SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection. 112-118 - Paul Nulty, David Lillis:
The UCD-Net System at SemEval-2020 Task 1: Temporal Referencing with Semantic Network Distances. 119-125 - Andrey Kutuzov, Mario Giulianelli:
UiO-UvA at SemEval-2020 Task 1: Contextualised Embeddings for Lexical Semantic Change Detection. 126-134 - Ádám Kovács, Kinga Gémes, András Kornai, Gábor Recski:
BMEAUT at SemEval-2020 Task 2: Lexical Entailment with Semantic Graphs. 135-141 - Hansi Hettiarachchi, Tharindu Ranasinghe:
BRUMS at SemEval-2020 Task 3: Contextualised Embeddings for Predicting the (Graded) Effect of Context in Word Similarity. 142-149 - Helena Gómez-Adorno, Gemma Bel-Enguix, Jorge Reyes-Magaña, Benjamín Moreno, Ramón Casillas, Daniel Vargas:
MineriaUNAM at SemEval-2020 Task 3: Predicting Contextual WordSimilarity Using a Centroid Based Approach and Word Embeddings. 150-157 - Aina Garí Soler, Marianna Apidianaki:
MULTISEM at SemEval-2020 Task 3: Fine-tuning BERT for Lexical Meaning. 158-165 - Li Tang:
UZH at SemEval-2020 Task 3: Combining BERT with WordNet Sense Embeddings to Predict Graded Word Similarity Changes. 166-170 - Nikolay Arefyev, Vasily Zhikov:
BOS at SemEval-2020 Task 1: Word Sense Induction via Lexical Substitution for Lexical Semantic Change Detection. 171-179 - Martin Pömsl, Roman Lyapin:
CIRCE at SemEval-2020 Task 1: Ensembling Context-Free and Context-Dependent Word Representations. 180-186 - David Rother, Thomas N. Haider, Steffen Eger:
CMCE at SemEval-2020 Task 1: Clustering on Manifolds of Contextualized Embeddings to Detect Historical Meaning Shifts. 187-193 - Frank D. Zamora-Reina, Felipe Bravo-Marquez:
DCC-Uchile at SemEval-2020 Task 1: Temporal Referencing Word Embeddings. 194-200 - Ehsaneddin Asgari, Christoph Ringlstetter, Hinrich Schütze:
EmbLexChange at SemEval-2020 Task 1: Unsupervised Embedding-based Detection of Lexical Semantic Changes. 201-207 - Vaibhav Jain:
GloVeInit at SemEval-2020 Task 1: Using GloVe Vector Initialization for Unsupervised Lexical Semantic Change Detection. 208-213 - Vani Kanjirangat, Sandra Mitrovic, Alessandro Antonucci, Fabio Rinaldi:
SST-BERT at SemEval-2020 Task 1: Semantic Shift Tracing by Clustering in BERT-based Embedding Spaces. 214-221 - Jinan Zhou, Jiaxin Li:
TemporalTeller at SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection with Temporal Referencing. 222-231 - Anna Karnysheva, Pia Schwarz:
TUE at SemEval-2020 Task 1: Detecting Semantic Change by Clustering Contextual Word Embeddings. 232-238 - Eleri Sarsfield, Harish Tayyar Madabushi:
UoB at SemEval-2020 Task 1: Automatic Identification of Novel Word Senses. 239-245 - Ondrej Prazák, Pavel Pribán, Stephen Taylor, Jakub Sido:
UWB at SemEval-2020 Task 1: Lexical Semantic Change Detection. 246-254 - Shike Wang, Yuchen Fan, Xiangying Luo, Dong Yu:
SHIKEBLCU at SemEval-2020 Task 2: An External Knowledge-enhanced Matrix for Multilingual and Cross-Lingual Lexical Entailment. 255-262 - Bradley Hauer, Amir Ahmad Habibi, Yixing Luan, Arnob Mallik, Grzegorz Kondrak:
UAlberta at SemEval-2020 Task 2: Using Translations to Predict Cross-Lingual Entailment. 263-269 - Mahmoud S. Abdel-Majeed, Marwan Torki:
AlexU-AUX-BERT at SemEval-2020 Task 3: Improving BERT Contextual Similarity Using Multiple Auxiliary Contexts. 270-274 - Pablo Gamallo:
CitiusNLP at SemEval-2020 Task 3: Comparing Two Approaches for Word Vector Contextualization. 275-280 - Weilong Chen, Xin Yuan, Sai Zhang, Jiehui Wu, Yanru Zhang, Yan Wang:
Ferryman at SemEval-2020 Task 3: Bert with TFIDF-Weighting for Predicting the Effect of Context in Word Similarity. 281-285 - Terufumi Morishita, Gaku Morio, Hiroaki Ozaki, Toshinori Miyoshi:
Hitachi at SemEval-2020 Task 3: Exploring the Representation Spaces of Transformers for Human Sense Word Similarity. 286-291 - Nour Al-Khdour, Mutaz Bni Younes, Malak Abdullah, Mohammad Al-Smadi:
JUSTMasters at SemEval-2020 Task 3: Multilingual Deep Learning Model to Predict the Effect of Context in Word Similarity. 292-300 - Wei Bao, Hongshu Che, Jiandong Zhang:
Will_Go at SemEval-2020 Task 3: An Accurate Model for Predicting the (Graded) Effect of Context in Word Similarity Based on BERT. 301-306 - Cunxiang Wang, Shuailong Liang, Yili Jin, Yilong Wang, Xiaodan Zhu, Yue Zhang:
SemEval-2020 Task 4: Commonsense Validation and Explanation. 307-321 - Xiaoyu Yang, Stephen Obadinma, Huasha Zhao, Qiong Zhang, Stan Matwin, Xiaodan Zhu:
SemEval-2020 Task 5: Counterfactual Recognition. 322-335 - Sasha Spala, Nicholas A. Miller, Franck Dernoncourt, Carl Dockhorn:
SemEval-2020 Task 6: Definition Extraction from Free Text with the DEFT Corpus. 336-345 - Luxi Xing, Yuqiang Xie, Yue Hu, Wei Peng:
IIE-NLP-NUT at SemEval-2020 Task 4: Guiding PLM with Prompt Template Reconstruction Strategy for ComVE. 346-353 - Xiao Ding, Dingkui Hao, Yuewei Zhang, Kuo Liao, Zhongyang Li, Bing Qin, Ting Liu:
HIT-SCIR at SemEval-2020 Task 5: Training Pre-trained Language Model with Pseudo-labeling Data for Counterfactuals Detection. 354-360 - Shelan S. Jeawak, Luis Espinosa Anke, Steven Schockaert:
Cardiff University at SemEval-2020 Task 6: Fine-tuning BERT for Domain-Specific Definition Classification. 361-366 - Anandh Konar, Chenyang Huang, Amine Trabelsi, Osmar R. Zaïane:
ANA at SemEval-2020 Task 4: MUlti-task learNIng for cOmmonsense reasoNing (UNION). 367-373 - Josef Jon, Martin Fajcik, Martin Docekal, Pavel Smrz:
BUT-FIT at SemEval-2020 Task 4: Multilingual Commonsense. 374-390 - Hongru Wang, Xiangru Tang, Sunny Lai, Kwong-Sak Leung, Jia Zhu, Gabriel Pui Cheong Fung, Kam-Fai Wong:
CUHK at SemEval-2020 Task 4: CommonSense Explanation, Reasoning and Prediction with Multi-task Learning. 391-400 - Qian Zhao, Siyu Tao, Jie Zhou, Linlin Wang, Xin Lin, Liang He:
ECNU-SenseMaker at SemEval-2020 Task 4: Leveraging Heterogeneous Knowledge Resources for Commonsense Validation and Explanation. 401-410 - Daming Lu:
Masked Reasoner at SemEval-2020 Task 4: Fine-Tuning RoBERTa for Commonsense Reasoning. 411-414 - Liu Pai:
QiaoNing at SemEval-2020 Task 4: Commonsense Validation and Explanation System Based on Ensemble of Language Model. 415-421 - Wiem Ben Rim, Naoaki Okazaki:
SWAGex at SemEval-2020 Task 4: Commonsense Explanation as Next Event Prediction. 422-429 - Thanet Markchom, Bhuvana Dhruva, Chandresh Pravin, Huizhi Liang:
UoR at SemEval-2020 Task 4: Pre-trained Sentence Transformer Models for Commonsense Validation and Explanation. 430-436 - Martin Fajcik, Josef Jon, Martin Docekal, Pavel Smrz:
BUT-FIT at SemEval-2020 Task 5: Automatic Detection of Counterfactual Statements with Deep Pre-trained Language Representation Models. 437-444 - MinGyou Sung, Parsa Bagherzadeh, Sabine Bergler:
CLaC at SemEval-2020 Task 5: Muli-task Stacked Bi-LSTMs. 445-450 - Rajaswa Patil, Veeky Baths:
CNRL at SemEval-2020 Task 5: Modelling Causal Reasoning in Language with Multi-Head Self-Attention Weights Based Counterfactual Detection. 451-457 - Anirudh Anil Ojha, Rohin Garg, Shashank Gupta, Ashutosh Modi:
IITK-RSA at SemEval-2020 Task 5: Detecting Counterfactuals. 458-467 - Hanna Abi Akl, Dominique Mariko, Estelle Labidurie:
Yseop at SemEval-2020 Task 5: Cascaded BERT Language Model for Counterfactual Statement Analysis. 468-478 - Fabien Caspani, Pirashanth Ratnamogan, Mathis Linger, Mhamed Hajaiej:
ACNLP at SemEval-2020 Task 6: A Supervised Approach for Definition Extraction. 479-486 - Adis Davletov, Nikolay Arefyev, Alexander Shatilov, Denis Gordeev, Alexey Rey:
Gorynych Transformer at SemEval-2020 Task 6: Multi-task Learning for Definition Extraction. 487-493 - Yice Zhang, Jiaxuan Lin, Yang Fan, Peng Jin, Yuanchao Liu, Bingquan Liu:
CN-HIT-IT.NLP at SemEval-2020 Task 4: Enhanced Language Representation with Multiple Knowledge Triples. 494-500 - Soumya Ranjan Dash, Sandeep Routray, Prateek Varshney, Ashutosh Modi:
CS-NET at SemEval-2020 Task 4: Siamese BERT for ComVE. 501-506 - Sirwe Saeedi, Aliakbar Panahi, Seyran Saeedi, Alvis Cheuk Ming Fong:
CS-NLP Team at SemEval-2020 Task 4: Evaluation of State-of-the-art NLP Deep Learning Architectures on Commonsense Reasoning Task. 507-515 - Yang Bai, Xiaobing Zhou:
DEEPYANG at SemEval-2020 Task 4: Using the Hidden Layer State of BERT Model for Differentiating Common Sense. 516-520 - Heba Al-Jarrah, Rahaf Al-hamouri, Mohammad Al-Smadi:
HR@JUST Team at SemEval-2020 Task 4: The Impact of RoBERTa Transformer for Evaluation Common Sense Understanding. 521-526 - Seung-Hoon Na, Jong-Hyeok Lee:
JBNU at SemEval-2020 Task 4: BERT and UniLM for Commonsense Validation and Explanation. 527-534 - Ali Fadel, Mahmoud Al-Ayyoub, Erik Cambria:
JUSTers at SemEval-2020 Task 4: Evaluating Transformer Models against Commonsense Validation and Explanation. 535-542 - Jiajing Wan, Xinting Huang:
KaLM at SemEval-2020 Task 4: Knowledge-aware Language Models for Comprehension and Generation. 543-550 - Khanddorj Mendbayar, Masaki Aono:
KDE SenseForce at SemEval-2020 Task 4: Exploiting BERT for Commonsense Validation and Explanation. 551-555 - Junyi Li, Bin Wang, Haiyan Ding:
Lijunyi at SemEval-2020 Task 4: An ALBERT Model Based Maximum Ensemble with Different Training Sizes and Depths for Commonsense Validation and Explanation. 556-561 - Shilei Liu, Yu Guo, Bochao Li, Feiliang Ren:
LMVE at SemEval-2020 Task 4: Commonsense Validation and Explanation Using Pretraining Language Model. 562-568 - Kris Collins, Max Grathwohl, Heba Ahmed:
Mxgra at SemEval-2020 Task 4: Common Sense Making with Next Token Prediction. 569-573 - Emran Al-Bashabsheh, Ayah Abu Aqouleh, Mohammad Al-Smadi:
NLP@JUST at SemEval-2020 Task 4: Ensemble Technique for BERT and Roberta to Evaluate Commonsense Validation. 574-579 - Rishivardhan K, Kayalvizhi S, Thenmozhi D, Raghav R., Kshitij Sharma:
SSN-NLP at SemEval-2020 Task 4: Text Classification and Generation on Common Sense Context Using Neural Networks. 580-584 - Vertika Srivastava, Sudeep Kumar Sahoo, Yeon Hyang Kim, Rohit R. R, Mayank Raj, Ajay Jaiswal:
Team Solomon at SemEval-2020 Task 4: Be Reasonable: Exploiting Large-scale Language Models for Commonsense Reasoning. 585-593 - Roweida Mohammed, Malak Abdullah:
TeamJUST at SemEval-2020 Task 4: Commonsense Validation and Explanation Using Ensembling Techniques. 594-600 - Don Teo:
TR at SemEval-2020 Task 4: Exploring the Limits of Language-model-based Common Sense Validation. 601-608 - Ciprian-Gabriel Cusmuliuc, Lucia Georgiana Coca, Adrian Iftene:
UAICS at SemEval-2020 Task 4: Using a Bidirectional Transformer for Task a. 609-613 - Kerenza Doxolodeo, Rahmad Mahendra:
UI at SemEval-2020 Task 4: Commonsense Validation and Explanation by Exploiting Contradiction. 614-619 - Yuhang Wu, Hao Wu:
Warren at SemEval-2020 Task 4: ALBERT and Multi-Task Learning for Commonsense Validation. 620-625 - Xiaozhi Ou, Hongling Li:
YNU-oxz at SemEval-2020 Task 4: Commonsense Validation Using BERT with Bidirectional GRU. 626-632 - Chang Liu, Dong Yu:
BLCU-NLP at SemEval-2020 Task 5: Data Augmentation for Efficient Counterfactual Detecting. 633-639 - Yang Bai, Xiaobing Zhou:
BYteam at SemEval-2020 Task 5: Detecting Counterfactual Statements with BERT and Ensembles. 640-644 - Len Yabloko:
ETHAN at SemEval-2020 Task 5: Modelling Causal Reasoning in Language Using Neuro-symbolic Cloud Computing. 645-652 - Weilong Chen, Yan Zhuang, Peng Wang, Feng Hong, Yan Wang, Yanru Zhang:
Ferryman as SemEval-2020 Task 5: Optimized BERT for Detecting Counterfactuals. 653-657 - Yaojie Lu, Annan Li, Hongyu Lin, Xianpei Han, Le Sun:
ISCAS at SemEval-2020 Task 5: Pre-trained Transformers for Counterfactual Statement Modeling. 658-663 - Junyi Li, Yuhang Wu, Bin Wang, Haiyan Ding:
Lee at SemEval-2020 Task 5: ALBERT Model Based on the Maximum Ensemble Strategy and Different Data Sampling Methods for Detecting Counterfactual Statements. 664-669 - Elvis Mboning Tchiaze, Damien Nouvel:
NLU-Co at SemEval-2020 Task 5: NLU/SVM Based Model Apply Tocharacterise and Extract Counterfactual Items on Raw Data. 670-676 - Pouria Babvey, Dario Borrelli, Yutong Zhao, Carlo Lipizzi:
Pheonix at SemEval-2020 Task 5: Masking the Labels Lubricates Models for Sequence Labeling. 677-682 - Xiaozhi Ou, Shengyan Liu, Hongling Li:
YNU-oxz at SemEval-2020 Task 5: Detecting Counterfactuals Based on Ordered Neurons LSTM and Hierarchical Attention Network. 683-689 - Huihui Zhang, Feiliang Ren:
BERTatDE at SemEval-2020 Task 6: Extracting Term-definition Pairs in Free Text Using Pre-trained Model. 690-696 - Jekaterina Kaparina, Anna Soboleva:
DeftPunk at SemEval-2020 Task 6: Using RNN-ensemble for the Sentence Classification. 697-703 - Marc Hübner, Christoph Alt, Robert Schwarzenberg, Leonhard Hennig:
Defx at SemEval-2020 Task 6: Joint Extraction of Concepts and Relations for Definition Extraction. 704-709 - Aadarsh Singh, Priyanshu Kumar, Aman Sinha:
DSC IIT-ISM at SemEval-2020 Task 6: Boosting BERT with Dependencies for Definition Extraction. 710-716 - Tharindu Ranasinghe, Alistair Plum, Constantin Orasan, Ruslan Mitkov:
RGCL at SemEval-2020 Task 6: Neural Approaches to DefinitionExtraction. 717-723 - Madeeswaran Kannan, Haemanth Santhi Ponnusamy:
TüKaPo at SemEval-2020 Task 6: Def(n)tly Not BERT: Definition Extraction Using pre-BERT Methods in a post-BERT World. 724-729 - Shu-Yi Xie, Jian Ma, Haiqin Yang, Lian-Xin Jiang, Yang Mo, Jian-Ping Shen:
UNIXLONG at SemEval-2020 Task 6: A Joint Model for Definition Extraction. 730-736 - Andrei-Marius Avram, Dumitru-Clementin Cercel, Costin-Gabriel Chiru:
UPB at SemEval-2020 Task 6: Pretrained Language Models for Definition Extraction. 737-745 - Nabil Hossain, John Krumm, Michael Gamon, Henry A. Kautz:
SemEval-2020 Task 7: Assessing Humor in Edited News Headlines. 746-758 - Chhavi Sharma, Deepesh Bhageria, William Scott, Srinivas PYKL, Amitava Das, Tanmoy Chakraborty, Viswanath Pulabaigari, Björn Gambäck:
SemEval-2020 Task 8: Memotion Analysis- the Visuo-Lingual Metaphor! 759-773 - Parth Patwa, Gustavo Aguilar, Sudipta Kar, Suraj Pandey, Srinivas PYKL, Björn Gambäck, Tanmoy Chakraborty, Thamar Solorio, Amitava Das:
SemEval-2020 Task 9: Overview of Sentiment Analysis of Code-Mixed Tweets. 774-790 - Terufumi Morishita, Gaku Morio, Hiroaki Ozaki, Toshinori Miyoshi:
Hitachi at SemEval-2020 Task 7: Stacking at Scale with Heterogeneous Language Models for Humor Recognition. 791-803 - Lisa Bonheme, Marek Grzes:
SESAM at SemEval-2020 Task 8: Investigating the Relationship between Image and Text in Sentiment Analysis of Memes. 804-816 - Jiaxiang Liu, Xuyi Chen, Shikun Feng, Shuohuan Wang, Xuan Ouyang, Yu Sun, Zhengjie Huang, Weiyue Su:
Kk2018 at SemEval-2020 Task 9: Adversarial Training for Code-Mixing Sentiment Classification. 817-823 - Kristian Nørgaard Jensen, Nicolaj Filrup Rasmussen, Thai Wang, Marco Placenti, Barbara Plank:
Buhscitu at SemEval-2020 Task 7: Assessing Humour in Edited News Headlines Using Hand-Crafted Features and Online Knowledge Bases. 824-832 - Ravi Theja Desetty, Ranit Chatterjee, Smita Ghaisas:
Hasyarasa at SemEval-2020 Task 7: Quantifying Humor as Departure from Expectedness. 833-842 - Martin Docekal, Martin Fajcik, Josef Jon, Pavel Smrz:
JokeMeter at SemEval-2020 Task 7: Convolutional Humor. 843-851 - Rida Miraj, Masaki Aono:
KDEhumor at SemEval-2020 Task 7: A Neural Network Model for Detecting Funniness in Dataset Humicroedit. 852-857 - Siddhant Mahurkar, Rajaswa Patil:
LRG at SemEval-2020 Task 7: Assessing the Ability of BERT and Derivative Models to Perform Short-Edits Based Humor Grading. 858-864 - Kayalvizhi S, D. Thenmozhi, Chandrabose Aravindan:
SSN_NLP at SemEval-2020 Task 7: Detecting Funniness Level Using Traditional Learning with Sentence Embeddings. 865-870 - Joseph Tomasulo, Jin Wang, Xuejie Zhang:
YNU-HPCC at SemEval-2020 Task 7: Using an Ensemble BiGRU Model to Evaluate the Humor of Edited News Titles. 871-875 - Pradyumna Gupta, Himanshu Gupta, Aman Sinha:
DSC IIT-ISM at SemEval-2020 Task 8: Bi-Fusion Techniques for Deep Meme Emotion Analysis. 876-884 - Arup Baruah, Kaushik Amar Das, Ferdous A. Barbhuiya, Kuntal Dey:
IIITG-ADBU at SemEval-2020 Task 8: A Multimodal Approach to Detect Offensive, Sarcastic and Humorous Memes. 885-890 - Ingroj Shrestha, Jonathan Rusert:
NLP_UIOWA at SemEval-2020 Task 8: You're Not the Only One Cursed with Knowledge - Multi Branch Model Memotion Analysis. 891-900 - Xiaoyu Guo, Jing Ma, Arkaitz Zubiaga:
NUAA-QMUL at SemEval-2020 Task 8: Utilizing BERT and DenseNet for Internet Meme Emotion Analysis. 901-907