08:50 - 09:00 Opening Remarks

09:00 - 10:30 Research Track

09:00 - 09:15 Ring That Bell: A Corpus and Method for Multimodal Metaphor Detection in Videos

Khalid Alnajjar, Mika Hämäläinen and Shuo Zhang

09:15 - 09:30 Food for Thought: How can we exploit contextual embeddings in the translation of idiomatic expressions?

Lukas Santing, Ryan Jean-Luc Sijstermans, Giacomo Anerdi, Pedro Jeuris, Marijn ten Thij and Riza Batista-Navarro

9:30 - 09:45 Distribution-Based Measures of Surprise for Creative Language: Experiments with Humor and Metaphor

Razvan C. Bunescu and Oseremen O. Uduehi

9:45 - 09:55 The Secret of Metaphor on Expressing Stronger Emotion

Yucheng Li, Frank Guerin and Chenghua Lin

09:55 - 10:05 Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning

Meghdut Sengupta, Milad Alshomary and Henning Wachsmuth

10:05 - 10:15 Can Yes-No Question-Answering Models be Useful for Few-Shot Metaphor Detection?

Lena Dankin, Kfir Bar and Nachum Dershowitz

10:15 - 10:25 On the Cusp of Comprehensibility: Can Language Models Distinguish Between Metaphors and Nonsense?

Bernadeta Griciute, Marc Tanti and Lucia Donatelli

10:30 - 11:00 Coffee Break

11:00 - 12:30 Research Track + Shared Tasks

11:00 - 11:10 A Report on the Euphemisms Detection Shared Task

Patrick Lee, Anna Feldman and Jing Peng

11:10 - 11:20 EUREKA: EUphemism Recognition Enhanced through Knn-based methods and Augmentation

Sedrick Scott Keh, Rohit Bharadwaj, Emmy Liu, Simone Tedeschi, Varun Gangal and Roberto Navigli

11:20 - 11:30 Detecting Euphemisms with Literal Descriptions and Visual Imagery

Ilker Kesen, Aykut Erdem, Erkut Erdem and Iacer Calixto

11:30 - 11:40 A Report on the FigLang 2022 Shared Task on Understanding Figurative Language

Arkadiy Saakyan, Tuhin Chakrabarty, Debanjan Ghosh and Smaranda Muresan

11:40 - 11:50 Just-DREAM-about-it: Figurative Language Understanding with DREAM- FLUTE

Yuling Gu, Yao Fu, Valentina Pyatkin, Ian Magnusson, Bhavana Dalvi Mishra and Peter Clark

11:50 - 12:00 Effective Cross-Task Transfer Learning for Explainable Natural Language Inference with T5

Irina Bigoulaeva, Rachneet Singh Sachdeva, Harish Tayyar Madabushi, Aline Villavicencio and Iryna Gurevych

12:00 - 12:15 Drum Up SUPPORT: Systematic Analysis of Image-Schematic Conceptual Metaphors

Lennart Wachowiak, Dagmar Gromann and Chao Xu

12:15 - 12: 30 Transfer Learning Parallel Metaphor using Bilingual Embeddings

Maria Berger

12:30 - 14:00 Lunch Break

14:00 - 15:00 Keynote Talk 1: Aline Villavicencio: Modelling Multiword Expressions and Idiomaticity: an Acid Test for Understanding

15:00 - 15:10 An insulin pump? Identifying figurative links in the construction of the drug lexicon

Antonio Reyes and Rafael Saldivar

15:10 - 15:20 Picard understanding Darmok: A Dataset and Model for Metaphor-Rich Translation in a Constructed Language

Peter A. Jansen and Jordan Boyd-Graber

15:20 - 15: 30 FigurativeQA: A Test Benchmark for Figurativeness Comprehension for Question Answering

Geetanjali Rakshit and Jeffrey Flanigan

15:30 - 16:00 Coffee Break

16:00 - 17:30 Poster Session (Shared Tasks + Findings)

TEDB System Description to a Shared Task on Euphemism Detection 2022

Peratham Wiriyathammabhum

A Prompt Based Approach for Euphemism Detection

Abulimiti Maimaitituoheti, Yang Yong and Fan Xiaochao

Euphemism Detection by Transformers and Relational Graph Attention Network

Yuting Wang, Yiyi Liu, Ruqing Zhang, Yixing Fan and Jiafeng Guo

Bayes at FigLang 2022 Euphemism Detection shared task: Cost-Sensitive Bayesian Fine-tuning and Venn-Abers Predictors for Robust Training under Class Skewed Distributions

Paul Trust, Kadusabe Provia and Kizito Omala

An Exploration of Linguistically-Driven and Transfer Learning Methods for Euphemism Detection

Devika Tiwari and Natalie Parde

Adversarial Perturbations Augmented Language Models for Euphemism Identification

Guneet Kohli, Prabsimran Kaur and Jatin Bedi

Exploring Euphemism Detection in Few-Shot and Zero-Shot Settings

Sedrick Scott Keh

SBU Figures It Out: Models Explain Figurative Language

Yash Kumar Lal and Mohaddeseh Bastan

NLP@UIT at FigLang-EMNLP 2022: A Divide-and-Conquer System For Shared Task On Understanding Figurative Language

Khoa Thi-Kim Phan, Duc-Vu Nguyen and Ngan Luu-Thuy Nguyen

Visualizing the Obvious: A Concreteness-based Ensemble Model for Noun Property Prediction

Yue Yang, Artemis Panagopoulou, Marianna Apidianaki, Mark Yatskar and Chris Callison-Burch

A Unified Framework for Pun Generation with Humor Principles

Yufei Tian, Divyanshu Arun Sheth and Nanyun Peng

Cards Against AI: Predicting Humor in a Fill-in-the-blank Party Game

Dan Ofer and Dafna Shahaf

Scientific and Creative Analogies in Pretrained Language Models

Tamara Czinczoll, Helen Yannakoudakis, Pushkar Mishra and Ekaterina Shutova

PoeLM: A Meter- and Rhyme-Controllable Language Model for Unsupervised Poetry

Aitor Ormazabal, Mikel Artetxe, Manex Agirrezabal, Aitor Soroa and Eneko Agirre

Systematicity in GPT-3's Interpretation of Novel English Noun Compounds

Siyan Li, Riley Carlson and Christopher Potts

Sarcasm Detection is Way Too Easy! An Empirical Comparison of Human and Machine

Ibrahim Abu Farha, Steven R. Wilson, Silviu Oprea and Walid Magdy

It's Better to Teach Fishing than Giving a Fish: An Auto-Augmented Structure-aware Generative Model for Metaphor Detection

Huawen Feng and Qianli Ma

17:30 - 17:55 Mini Break

17:55 - 19:00 Keynote Talk 2: Penny M. Pexman: Irony Acquisition: How Children Learn to Detect Sarcasm