Abstract is missing.
- A Report on the 2020 Sarcasm Detection Shared TaskDebanjan Ghosh, Avijit Vajpayee, Smaranda Muresan. 1-11 [doi]
- Augmenting Data for Sarcasm Detection with Unlabeled Conversation ContextHankyol Lee, Youngjae Yu, Gunhee Kim. 12-17 [doi]
- A Report on the 2020 VUA and TOEFL Metaphor Detection Shared TaskChee Wee Leong, Beata Beigman Klebanov, Chris Hamill, Egon Stemle, Rutuja Ubale, Xianyang Chen. 18-29 [doi]
- DeepMet: A Reading Comprehension Paradigm for Token-level Metaphor DetectionChuandong Su, Fumiyo Fukumoto, Xiaoxi Huang, Jiyi Li, Rongbo Wang, Zhiqun Chen. 30-39 [doi]
- Context-Driven Satirical News GenerationZachary Horvitz, Nam Do, Michael L. Littman. 40-50 [doi]
- Sarcasm Detection using Context Separators in Online DiscourseTanvi Dadu, Kartikey Pant. 51-55 [doi]
- Sarcasm Detection in Tweets with BERT and GloVe EmbeddingsAkshay Khatri, Pranav P. 56-60 [doi]
- C-Net: Contextual Network for Sarcasm DetectionAmit Kumar Jena, Aman Sinha, Rohit Agarwal. 61-66 [doi]
- Applying Transformers and Aspect-based Sentiment Analysis approaches on Sarcasm DetectionTaha Shangipour Ataei, Soroush Javdan, Behrouz Minaei-Bidgoli. 67-71 [doi]
- Sarcasm Identification and Detection in Conversion Context using BERTA. Kalaivani, D. Thenmozhi. 72-76 [doi]
- Neural Sarcasm Detection using Conversation ContextNikhil Jaiswal. 77-82 [doi]
- Context-Aware Sarcasm Detection Using BERTArup Baruah, Kaushik Amar Das, Ferdous A. Barbhuiya, Kuntal Dey. 83-87 [doi]
- Transformers on Sarcasm Detection with ContextAmardeep Kumar, Vivek Anand. 88-92 [doi]
- A Novel Hierarchical BERT Architecture for Sarcasm DetectionHimani Srivastava, Vaibhav Varshney, Surabhi Kumari, Saurabh Srivastava. 93-97 [doi]
- Detecting Sarcasm in Conversation Context Using Transformer-Based ModelsAdithya Avvaru, Sanath Vobilisetty, Radhika Mamidi. 98-103 [doi]
- Using Conceptual Norms for Metaphor DetectionMingyu Wan, Kathleen Ahrens, Emmanuele Chersoni, Menghan Jiang, Qi Su, Rong Xiang, Chu-Ren Huang. 104-109 [doi]
- ALBERT-BiLSTM for Sequential Metaphor DetectionShuqun Li, Jingjie Zeng, Jinhui Zhang, Tao Peng, Liang Yang 0003, Hongfei Lin. 110-115 [doi]
- Character aware models with similarity learning for metaphor detectionTarun Kumar, Yashvardhan Sharma. 116-125 [doi]
- Sky + Fire = Sunset. Exploring Parallels between Visually Grounded Metaphors and Image ClassifiersYuri Bizzoni, Simon Dobnik. 126-135 [doi]
- Recognizing Euphemisms and Dysphemisms Using Sentiment AnalysisChristian Felt, Ellen Riloff. 136-145 [doi]
- IlliniMet: Illinois System for Metaphor Detection with Contextual and Linguistic InformationHongyu Gong, Kshitij Gupta, Akriti Jain, Suma Bhat. 146-153 [doi]
- Adaptation of Word-Level Benchmark Datasets for Relation-Level Metaphor IdentificationOmnia Zayed, John Philip McCrae, Paul Buitelaar. 154-164 [doi]
- Generating Ethnographic Models from Communities' Online DataTomek Strzalkowski, Anna Newheiser, Nathan Kemper, Ning Sa, Bharvee Acharya, Gregorios A. Katsios. 165-175 [doi]
- Oxymorons: a preliminary corpus investigationMarta La Pietra, Francesca Masini. 176-185 [doi]
- Can Humor Prediction Datasets be used for Humor Generation? Humorous Headline Generation via Style TransferOrion Weller, Nancy Fulda, Kevin D. Seppi. 186-191 [doi]
- Evaluating a Bi-LSTM Model for Metaphor Detection in TOEFL EssaysKevin Kuo, Marine Carpuat. 192-196 [doi]
- Neural Metaphor Detection with a Residual biLSTM-CRF ModelAndrés Torres Rivera, Antoni Oliver 0001, Salvador Climent 0001, Marta Coll-Florit. 197-203 [doi]
- Augmenting Neural Metaphor Detection with ConcretenessGhadi Alnafesah, Harish Tayyar Madabushi, Mark Lee. 204-210 [doi]
- Supervised Disambiguation of German Verbal Idioms with a BiLSTM ArchitectureRafael Ehren, Timm Lichte, Laura Kallmeyer, Jakub Waszczuk. 211-220 [doi]
- Metaphor Detection using Context and ConcretenessRowan Hall Maudslay, Tiago Pimentel, Ryan Cotterell, Simone Teufel. 221-226 [doi]
- Being neighbourly: Neural metaphor identification in discourseVerna Dankers, Karan Malhotra, Gaurav Kudva, Volodymyr Medentsiy, Ekaterina Shutova. 227-234 [doi]
- Go Figure! Multi-task transformer-based architecture for metaphor detection using idioms: ETS team in 2020 metaphor shared taskXianyang Chen, Chee Wee Leong, Michael Flor, Beata Beigman Klebanov. 235-243 [doi]
- Metaphor Detection using Ensembles of Bidirectional Recurrent Neural NetworksJennifer Brooks, Abdou Youssef. 244-249 [doi]
- Metaphor Detection Using Contextual Word Embeddings From TransformersJerry Liu, Nathan O'Hara, Alexander Rubin, Rachel Lea Draelos, Cynthia Rudin. 250-255 [doi]
- Testing the role of metadata in metaphor identificationEgon Stemle, Alexander Onysko. 256-263 [doi]
- Sarcasm Detection Using an Ensemble ApproachJens Lemmens, Ben Burtenshaw, Ehsan Lotfi, Ilia Markov, Walter Daelemans. 264-269 [doi]
- A Transformer Approach to Contextual Sarcasm Detection in TwitterHunter Gregory, Steven Li, Pouya Mohammadi, Natalie Tarn, Rachel Lea Draelos, Cynthia Rudin. 270-275 [doi]
- Transformer-based Context-aware Sarcasm Detection in Conversation Threads from Social MediaXiangjue Dong, Changmao Li, Jinho D. Choi. 276-280 [doi]