@inproceedings{hutchinson-etal-2022-underspecification,
title = "Underspecification in Scene Description-to-Depiction Tasks",
author = "Hutchinson, Ben and
Baldridge, Jason and
Prabhakaran, Vinodkumar",
editor = "He, Yulan and
Ji, Heng and
Li, Sujian and
Liu, Yang and
Chang, Chua-Hui",
booktitle = "Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
month = nov,
year = "2022",
address = "Online only",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.aacl-main.86/",
doi = "10.18653/v1/2022.aacl-main.86",
pages = "1172--1184",
abstract = "Questions regarding implicitness, ambiguity and underspecification are crucial for understanding the task validity and ethical concerns of multimodal image+text systems, yet have received little attention to date. This position paper maps out a conceptual framework to address this gap, focusing on systems which generate images depicting scenes from scene descriptions. In doing so, we account for how texts and images convey meaning differently. We outline a set of core challenges concerning textual and visual ambiguity, as well as risks that may be amplified by ambiguous and underspecified elements. We propose and discuss strategies for addressing these challenges, including generating visually ambiguous images, and generating a set of diverse images."
}
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<abstract>Questions regarding implicitness, ambiguity and underspecification are crucial for understanding the task validity and ethical concerns of multimodal image+text systems, yet have received little attention to date. This position paper maps out a conceptual framework to address this gap, focusing on systems which generate images depicting scenes from scene descriptions. In doing so, we account for how texts and images convey meaning differently. We outline a set of core challenges concerning textual and visual ambiguity, as well as risks that may be amplified by ambiguous and underspecified elements. We propose and discuss strategies for addressing these challenges, including generating visually ambiguous images, and generating a set of diverse images.</abstract>
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%0 Conference Proceedings
%T Underspecification in Scene Description-to-Depiction Tasks
%A Hutchinson, Ben
%A Baldridge, Jason
%A Prabhakaran, Vinodkumar
%Y He, Yulan
%Y Ji, Heng
%Y Li, Sujian
%Y Liu, Yang
%Y Chang, Chua-Hui
%S Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
%D 2022
%8 November
%I Association for Computational Linguistics
%C Online only
%F hutchinson-etal-2022-underspecification
%X Questions regarding implicitness, ambiguity and underspecification are crucial for understanding the task validity and ethical concerns of multimodal image+text systems, yet have received little attention to date. This position paper maps out a conceptual framework to address this gap, focusing on systems which generate images depicting scenes from scene descriptions. In doing so, we account for how texts and images convey meaning differently. We outline a set of core challenges concerning textual and visual ambiguity, as well as risks that may be amplified by ambiguous and underspecified elements. We propose and discuss strategies for addressing these challenges, including generating visually ambiguous images, and generating a set of diverse images.
%R 10.18653/v1/2022.aacl-main.86
%U https://aclanthology.org/2022.aacl-main.86/
%U https://doi.org/10.18653/v1/2022.aacl-main.86
%P 1172-1184
Markdown (Informal)
[Underspecification in Scene Description-to-Depiction Tasks](https://aclanthology.org/2022.aacl-main.86/) (Hutchinson et al., AACL-IJCNLP 2022)
ACL
- Ben Hutchinson, Jason Baldridge, and Vinodkumar Prabhakaran. 2022. Underspecification in Scene Description-to-Depiction Tasks. In Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 1172–1184, Online only. Association for Computational Linguistics.