@inproceedings{saakyan-etal-2022-report,
title = "A Report on the {F}ig{L}ang 2022 Shared Task on Understanding Figurative Language",
author = "Saakyan, Arkadiy and
Chakrabarty, Tuhin and
Ghosh, Debanjan and
Muresan, Smaranda",
editor = "Ghosh, Debanjan and
Beigman Klebanov, Beata and
Muresan, Smaranda and
Feldman, Anna and
Poria, Soujanya and
Chakrabarty, Tuhin",
booktitle = "Proceedings of the 3rd Workshop on Figurative Language Processing (FLP)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.flp-1.26",
doi = "10.18653/v1/2022.flp-1.26",
pages = "178--183",
abstract = "We present the results of the Shared Task on Understanding Figurative Language that we conducted as a part of the 3rd Workshop on Figurative Language Processing (FigLang 2022) at EMNLP 2022. The shared task is based on the FLUTE dataset (Chakrabarty et al., 2022), which consists of NLI pairs containing figurative language along with free text explanations for each NLI instance. The task challenged participants to build models that are able to not only predict the right label for a figurative NLI instance, but also generate a convincing free-text explanation. The participants were able to significantly improve upon provided baselines in both automatic and human evaluation settings. We further summarize the submitted systems and discuss the evaluation results.",
}
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%0 Conference Proceedings
%T A Report on the FigLang 2022 Shared Task on Understanding Figurative Language
%A Saakyan, Arkadiy
%A Chakrabarty, Tuhin
%A Ghosh, Debanjan
%A Muresan, Smaranda
%Y Ghosh, Debanjan
%Y Beigman Klebanov, Beata
%Y Muresan, Smaranda
%Y Feldman, Anna
%Y Poria, Soujanya
%Y Chakrabarty, Tuhin
%S Proceedings of the 3rd Workshop on Figurative Language Processing (FLP)
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates (Hybrid)
%F saakyan-etal-2022-report
%X We present the results of the Shared Task on Understanding Figurative Language that we conducted as a part of the 3rd Workshop on Figurative Language Processing (FigLang 2022) at EMNLP 2022. The shared task is based on the FLUTE dataset (Chakrabarty et al., 2022), which consists of NLI pairs containing figurative language along with free text explanations for each NLI instance. The task challenged participants to build models that are able to not only predict the right label for a figurative NLI instance, but also generate a convincing free-text explanation. The participants were able to significantly improve upon provided baselines in both automatic and human evaluation settings. We further summarize the submitted systems and discuss the evaluation results.
%R 10.18653/v1/2022.flp-1.26
%U https://aclanthology.org/2022.flp-1.26
%U https://doi.org/10.18653/v1/2022.flp-1.26
%P 178-183
Markdown (Informal)
[A Report on the FigLang 2022 Shared Task on Understanding Figurative Language](https://aclanthology.org/2022.flp-1.26) (Saakyan et al., Fig-Lang 2022)
ACL