All times are Seattle time, and may still change. Note for presenters: please be available during the next Q&A session after your presentation.

Thursday July 9, 2020

Session 1

06:00 Opening remarks

06:05 A Report on the 2020 Sarcasm Detection Shared Task

Debanjan Ghosh¹, Avijit Vajpayee¹, Smaranda Muresan²

¹Educational Testing Service, ²Columbia University

06:20 Augmenting Data for Sarcasm Detection with Unlabeled Conversation Context

Hankyol Lee¹, Youngjae Yu², Gunhee Kim²

¹RippleAI, ²RippleAI & SNU

06:35 A Report on the 2020 VUA and TOEFL Metaphor Detection Shared Task

Chee Wee (Ben) Leong¹, Beata Beigman Klebanov¹, Chris Hamill¹, Egon Stemle², Rutuja Ubale¹, Xianyang Chen¹

¹Educational Testing Service, ²Eurac Research

06:50 DeepMet: A Reading Comprehension Paradigm for Token-level Metaphor Detection

Chuandong Su¹, Fumiyo Fukumoto², Xiaoxi Huang¹, Jiyi Li², Rongbo Wang¹, Zhiqun Chen¹

¹Hangzhou Dianzi University, ²University of Yamanashi

07:05 Context-Driven Satirical News Generation

Zachary Horvitz, Nam Do, Michael L. Littman

Brown University

07:20 Coffee break

07:40 Sarcasm Detection using Context Separators in Online Discourse

TANVI DADU¹ and Kartikey Pant²

¹Netaji Subhas Institute of Technology, New Delhi, ²IIIT, Hyderabad

07:45 Sarcasm Detection in Tweets with BERT and GloVe Embeddings

Akshay Khatri and Pranav P

National Institute of Technology Karnataka

07:50 C-Net: Contextual Network for Sarcasm Detection

Amit Kumar Jena, Aman Sinha, Rohit Agarwal

Indian Institute of Technology (ISM) Dhanbad

07:55 Q & A session

08:00 Applying Transformers and Aspect-based Sentiment Analysis approaches on Sarcasm Detection

Taha Shangipour ataei, Soroush Javdan, Behrouz Minaei-Bidgoli

Computer Engineering Department, Iran University of Science and Technology

08:05 Sarcasm Identification and Detection in Conversion Context using BERT

kalaivani A and Thenmozhi D

SSN College of Engineering

08:10 Neural Sarcasm Detection using Conversation Context

Nikhil Jaiswal

TCS Research

08:15 Q & A session

08:20 Coffee break

08:40 Context-Aware Sarcasm Detection Using BERT

Arup Baruah¹, Kaushik Das¹, Ferdous Barbhuiya¹, Kuntal Dey²

¹Indian Institute of Information Technology, ²IBM Research, New Delhi

08:45 Transformers on Sarcasm Detection with Context

Amardeep Kumar¹ and Vivek Anand²

¹Indian Institute of Technology (Indian School of Mines), Dhanbad, ²IIIT Hyderabad, India

08:50 A Novel Hierarchical BERT Architecture for Sarcasm Detection

Himani Srivastava, Vaibhav Varshney, Surabhi Kumari, Saurabh Srivastava

TCS Research

08:55 Q & A session

09:00 Detecting Sarcasm in Conversation Context Using Transformer-Based Models

Adithya Avvaru¹, Sanath Vobilisetty¹, Radhika Mamidi²

¹Teradata, ²IIIT Hyderabad

09:05 Using Conceptual Norms for Metaphor Detection

Mingyu WAN¹, Kathleen Ahrens¹, Emmanuele Chersoni², Menghan Jiang², Qi Su³, Rong Xiang², Chu-Ren Huang²

¹The Hong Kong Polytechnic University, ²The Hong Kong Polytechnic Universiy, ³Peking University

09:10 ALBERT-BiLSTM for Sequential Metaphor Detection

Shuqun Li, Jingjie Zeng, Jinhui Zhang, Tao Peng, Liang Yang, Hongfei Lin

Dalian University of Technology

09:15 Character aware models with similarity learning for metaphor detection

Tarun Kumar and Yashvardhan Sharma

Birla Institute of Technology and Science

09:20 Q & A session

Session 2

10:00 Sky + Fire = Sunset. Exploring Parallels between Visually Grounded Metaphors and Image Classifiers

Yuri Bizzoni¹ and Simon Dobnik²

¹University of Saarland, ²University of Gothenburg

10:15 Recognizing Euphemisms and Dysphemisms Using Sentiment Analysis

Christian Felt and Ellen Riloff

University of Utah

10:30 IlliniMet: Illinois System for Metaphor Detection with Contextual and Linguistic Information

Hongyu Gong¹, Kshitij Gupta¹, Akriti Jain², Suma Bhat³

¹University of Illinois at Urbana-Champaign, ²University of Illinois at Urbana-Chamapaign, ³University of Illinois, Urbana-Champaign

10:35 Adaptation of Word-Level Benchmark Datasets for Relation-Level Metaphor Identification

Omnia Zayed¹, John Philip McCrae², Paul Buitelaar³

¹PhD Student - Insight Centre for Data Analytics - National University of Ireland Galway, ²Insight Center for Data Analytics, National University of Ireland Galway, ³Data Science Institute, National University of Ireland Galway

10:40 Generating Ethnographic Models from Communities’ Online Data

Tomek Strzalkowski¹, Anna Newheiser², Nathan Kemper², Ning Sa², Bharvee Acharya², Gregorios Katsios¹

¹RPI, ²SUNY Albany

10:45 Q & A session

10:50 Oxymorons: a preliminary corpus investigation

Marta La Pietra and Francesca Masini

University of Bologna

10:55 Can Humor Prediction Datasets be used for Humor Generation? Humorous Headline Generation via Style Transfer

Orion Weller, Nancy Fulda, Kevin Seppi

Brigham Young University

11:00 Evaluating a Bi-LSTM Model for Metaphor Detection in TOEFL Essays

Kevin Kuo¹ and Marine Carpuat²

¹University of Maryland, College Park, ²University of Maryland

11:05 Q & A session

11:10 Coffee break

11:30 Neural Metaphor Detection with a Residual biLSTM-CRF Model

Andrés Torres Rivera, Antoni Oliver, Salvador Climent, Marta Coll-Florit

Universitat Oberta de Catalunya

11:35 Augmenting Neural Metaphor Detection with Concreteness

Ghadi Alnafesah¹, Harish Tayyar Madabushi², Mark Lee²

¹University of Birmingham, Qassim University, ²University of Birmingham

11:40 Supervised Disambiguation of German Verbal Idioms with a BiLSTM Architecture

Rafael Ehren¹, Timm Lichte², Laura Kallmeyer³, Jakub Waszczuk³

¹Heinrich-Heine-Universität Düsseldorf, ²University of Tübingen, ³University of Duesseldorf

11:45 Q & A session

11:50 Metaphor Detection using Context and Concreteness

Rowan Hall Maudslay¹, Tiago Pimentel¹, Ryan Cotterell², Simone Teufel³

¹University of Cambridge, ²Johns Hopkins University, ³Cambridge University

11:55 Being neighbourly: Neural metaphor identification in discourse

Verna Dankers, Karan Malhotra, Gaurav Kudva, Volodymyr Medentsiy, Ekaterina Shutova

University of Amsterdam

12:00 Go Figure! Multi-task transformer-based architecture for metaphor detection using idioms: ETS team in 2020 metaphor shared task

Xianyang Chen, Chee Wee (Ben) Leong, Michael Flor, Beata Beigman Klebanov

Educational Testing Service

12:05 Q & A session

12:10 Metaphor Detection using Ensembles of Bidirectional Recurrent Neural Networks

Jennifer Brooks and Abdou Youssef

George Washington University

12:15 Metaphor Detection Using Contextual Word Embeddings From Transformers

Jerry Liu, Nathan O'Hara, Alexander Rubin, Rachel Draelos, Cynthia Rudin

Duke University

12:20 Testing the role of metadata in metaphor identification

Egon Stemle¹ and Alexander Onysko²

¹Eurac Research, ²University of Klagenfurt

12:25 Q & A session

12:30 Coffee break

12:50 Sarcasm Detection Using an Ensemble Approach

Jens Lemmens¹, Ben Burtenshaw¹, Ehsan Lotfi¹, Ilia Markov², Walter Daelemans²

¹University of Antwerp, ²University of Antwerp, CLiPS

12:55 A Transformer Approach to Contextual Sarcasm Detection in Twitter

Hunter Gregory, Steven Li, Pouya Mohammadi, Natalie Tarn, Rachel Draelos, Cynthia Rudin

Duke University

13:00 Transformer-based Context-aware Sarcasm Detection in Conversation Threads from Social Media

Xiangjue Dong, Changmao Li, Jinho D. Choi

Emory University

13:05 Q & A session

13:10 Closing discussion

13:30 Coffee break

Keynote

14:00 Marilyn Walker: Generating Expressive Language by Mining User Reviews