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ORCID2nd Fig-Lang@ACL 2020: Online Conference
- Beata Beigman Klebanov, Ekaterina Shutova, Patricia Lichtenstein, Smaranda Muresan, Chee Wee Leong, Anna Feldman, Debanjan Ghosh:
Proceedings of the Second Workshop on Figurative Language Processing, Fig-Lang@ACL 2020, Online, July 9, 2020. Association for Computational Linguistics 2020, ISBN 978-1-952148-12-5 - Debanjan Ghosh, Avijit Vajpayee, Smaranda Muresan:
A Report on the 2020 Sarcasm Detection Shared Task. 1-11 - Hankyol Lee, Youngjae Yu, Gunhee Kim:
Augmenting Data for Sarcasm Detection with Unlabeled Conversation Context. 12-17 - Chee Wee Leong, Beata Beigman Klebanov, Chris Hamill, Egon Stemle, Rutuja Ubale, Xianyang Chen:
A Report on the 2020 VUA and TOEFL Metaphor Detection Shared Task. 18-29 - Chuandong Su, Fumiyo Fukumoto, Xiaoxi Huang, Jiyi Li, Rongbo Wang, Zhiqun Chen:
DeepMet: A Reading Comprehension Paradigm for Token-level Metaphor Detection. 30-39 - Zachary Horvitz, Nam Do, Michael L. Littman:
Context-Driven Satirical News Generation. 40-50 - Tanvi Dadu, Kartikey Pant:
Sarcasm Detection using Context Separators in Online Discourse. 51-55 - Akshay Khatri, Pranav P:
Sarcasm Detection in Tweets with BERT and GloVe Embeddings. 56-60 - Amit Kumar Jena, Aman Sinha, Rohit Agarwal
:
C-Net: Contextual Network for Sarcasm Detection. 61-66 - Taha Shangipour Ataei, Soroush Javdan, Behrouz Minaei-Bidgoli:
Applying Transformers and Aspect-based Sentiment Analysis approaches on Sarcasm Detection. 67-71 - Kalaivani Adaikkan, Durairaj Thenmozhi:
Sarcasm Identification and Detection in Conversion Context using BERT. 72-76 - Nikhil Jaiswal:
Neural Sarcasm Detection using Conversation Context. 77-82 - Arup Baruah, Kaushik Amar Das, Ferdous A. Barbhuiya, Kuntal Dey:
Context-Aware Sarcasm Detection Using BERT. 83-87 - Amardeep Kumar, Vivek Anand:
Transformers on Sarcasm Detection with Context. 88-92 - Himani Srivastava, Vaibhav Varshney, Surabhi Kumari, Saurabh Srivastava:
A Novel Hierarchical BERT Architecture for Sarcasm Detection. 93-97 - Adithya Avvaru, Sanath Vobilisetty, Radhika Mamidi:
Detecting Sarcasm in Conversation Context Using Transformer-Based Models. 98-103 - Mingyu Wan, Kathleen Ahrens, Emmanuele Chersoni, Menghan Jiang, Qi Su, Rong Xiang, Chu-Ren Huang:
Using Conceptual Norms for Metaphor Detection. 104-109 - Shuqun Li, Jingjie Zeng, Jinhui Zhang, Tao Peng, Liang Yang, Hongfei Lin:
ALBERT-BiLSTM for Sequential Metaphor Detection. 110-115 - Tarun Kumar, Yashvardhan Sharma:
Character aware models with similarity learning for metaphor detection. 116-125 - Yuri Bizzoni, Simon Dobnik:
Sky + Fire = Sunset. Exploring Parallels between Visually Grounded Metaphors and Image Classifiers. 126-135 - Christian Felt, Ellen Riloff:
Recognizing Euphemisms and Dysphemisms Using Sentiment Analysis. 136-145 - Hongyu Gong, Kshitij Gupta, Akriti Jain, Suma Bhat:
IlliniMet: Illinois System for Metaphor Detection with Contextual and Linguistic Information. 146-153 - Omnia Zayed, John Philip McCrae, Paul Buitelaar:
Adaptation of Word-Level Benchmark Datasets for Relation-Level Metaphor Identification. 154-164 - Tomek Strzalkowski, Anna Newheiser, Nathan Kemper, Ning Sa, Bharvee Acharya, Gregorios A. Katsios:
Generating Ethnographic Models from Communities' Online Data. 165-175 - Marta La Pietra, Francesca Masini:
Oxymorons: a preliminary corpus investigation. 176-185 - Orion Weller, Nancy Fulda, Kevin D. Seppi:
Can Humor Prediction Datasets be used for Humor Generation? Humorous Headline Generation via Style Transfer. 186-191 - Kevin Kuo, Marine Carpuat:
Evaluating a Bi-LSTM Model for Metaphor Detection in TOEFL Essays. 192-196 - Andrés Torres Rivera, Antoni Oliver, Salvador Climent, Marta Coll-Florit:
Neural Metaphor Detection with a Residual biLSTM-CRF Model. 197-203 - Ghadi Alnafesah, Harish Tayyar Madabushi, Mark Lee:
Augmenting Neural Metaphor Detection with Concreteness. 204-210 - Rafael Ehren, Timm Lichte, Laura Kallmeyer, Jakub Waszczuk:
Supervised Disambiguation of German Verbal Idioms with a BiLSTM Architecture. 211-220 - Rowan Hall Maudslay, Tiago Pimentel, Ryan Cotterell, Simone Teufel:
Metaphor Detection using Context and Concreteness. 221-226 - Verna Dankers, Karan Malhotra, Gaurav Kudva, Volodymyr Medentsiy, Ekaterina Shutova:
Being neighbourly: Neural metaphor identification in discourse. 227-234 - Xianyang Chen, Chee Wee Leong, Michael Flor, Beata Beigman Klebanov:
Go Figure! Multi-task transformer-based architecture for metaphor detection using idioms: ETS team in 2020 metaphor shared task. 235-243 - Jennifer Brooks, Abdou Youssef:
Metaphor Detection using Ensembles of Bidirectional Recurrent Neural Networks. 244-249 - Jerry Liu, Nathan O'Hara, Alexander Rubin, Rachel Lea Draelos, Cynthia Rudin:
Metaphor Detection Using Contextual Word Embeddings From Transformers. 250-255 - Egon Stemle, Alexander Onysko:
Testing the role of metadata in metaphor identification. 256-263 - Jens Lemmens, Ben Burtenshaw, Ehsan Lotfi, Ilia Markov, Walter Daelemans:
Sarcasm Detection Using an Ensemble Approach. 264-269 - Hunter Gregory, Steven Li, Pouya Mohammadi, Natalie Tarn, Rachel Lea Draelos, Cynthia Rudin:
A Transformer Approach to Contextual Sarcasm Detection in Twitter. 270-275 - Xiangjue Dong, Changmao Li, Jinho D. Choi:
Transformer-based Context-aware Sarcasm Detection in Conversation Threads from Social Media. 276-280
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