@inproceedings{nobakhtian-etal-2023-iust,
title = "{IUST} at {I}mage{A}rg: The First Shared Task in Multimodal Argument Mining",
author = "Nobakhtian, Melika and
Zamaninejad, Ghazal and
Moosavi Monazzah, Erfan and
Eetemadi, Sauleh",
editor = "Alshomary, Milad and
Chen, Chung-Chi and
Muresan, Smaranda and
Park, Joonsuk and
Romberg, Julia",
booktitle = "Proceedings of the 10th Workshop on Argument Mining",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.argmining-1.13",
doi = "10.18653/v1/2023.argmining-1.13",
pages = "133--138",
abstract = "ImageArg is a shared task at the 10th ArgMining Workshop at EMNLP 2023. It leverages the ImageArg dataset to advance multimodal persuasiveness techniques. This challenge comprises two distinct subtasks: 1) Argumentative Stance (AS) Classification: Assessing whether a given tweet adopts an argumentative stance. 2) Image Persuasiveness (IP) Classification: Determining if the tweet image enhances the persuasive quality of the tweet. We conducted various experiments on both subtasks and ranked sixth out of the nine participating teams.",
}
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<abstract>ImageArg is a shared task at the 10th ArgMining Workshop at EMNLP 2023. It leverages the ImageArg dataset to advance multimodal persuasiveness techniques. This challenge comprises two distinct subtasks: 1) Argumentative Stance (AS) Classification: Assessing whether a given tweet adopts an argumentative stance. 2) Image Persuasiveness (IP) Classification: Determining if the tweet image enhances the persuasive quality of the tweet. We conducted various experiments on both subtasks and ranked sixth out of the nine participating teams.</abstract>
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%0 Conference Proceedings
%T IUST at ImageArg: The First Shared Task in Multimodal Argument Mining
%A Nobakhtian, Melika
%A Zamaninejad, Ghazal
%A Moosavi Monazzah, Erfan
%A Eetemadi, Sauleh
%Y Alshomary, Milad
%Y Chen, Chung-Chi
%Y Muresan, Smaranda
%Y Park, Joonsuk
%Y Romberg, Julia
%S Proceedings of the 10th Workshop on Argument Mining
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F nobakhtian-etal-2023-iust
%X ImageArg is a shared task at the 10th ArgMining Workshop at EMNLP 2023. It leverages the ImageArg dataset to advance multimodal persuasiveness techniques. This challenge comprises two distinct subtasks: 1) Argumentative Stance (AS) Classification: Assessing whether a given tweet adopts an argumentative stance. 2) Image Persuasiveness (IP) Classification: Determining if the tweet image enhances the persuasive quality of the tweet. We conducted various experiments on both subtasks and ranked sixth out of the nine participating teams.
%R 10.18653/v1/2023.argmining-1.13
%U https://aclanthology.org/2023.argmining-1.13
%U https://doi.org/10.18653/v1/2023.argmining-1.13
%P 133-138
Markdown (Informal)
[IUST at ImageArg: The First Shared Task in Multimodal Argument Mining](https://aclanthology.org/2023.argmining-1.13) (Nobakhtian et al., ArgMining-WS 2023)
ACL