@inproceedings{oguz-etal-2022-chop,
title = "Chop and Change: Anaphora Resolution in Instructional Cooking Videos",
author = "Oguz, Cennet and
Kruijff-Korbayova, Ivana and
Vincent, Emmanuel and
Denis, Pascal and
van Genabith, Josef",
editor = "He, Yulan and
Ji, Heng and
Li, Sujian and
Liu, Yang and
Chang, Chua-Hui",
booktitle = "Findings of the Association for Computational Linguistics: AACL-IJCNLP 2022",
month = nov,
year = "2022",
address = "Online only",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.findings-aacl.34/",
doi = "10.18653/v1/2022.findings-aacl.34",
pages = "364--374",
abstract = "Linguistic ambiguities arising from changes in entities in action flows are a key challenge in instructional cooking videos. In particular, temporally evolving entities present rich and to date understudied challenges for anaphora resolution. For example {\textquotedblleft}oil{\textquotedblright} mixed with {\textquotedblleft}salt{\textquotedblright} is later referred to as a {\textquotedblleft}mixture{\textquotedblright}. In this paper we propose novel annotation guidelines to annotate recipes for the anaphora resolution task, reflecting change in entities. Moreover, we present experimental results for end-to-end multimodal anaphora resolution with the new annotation scheme and propose the use of temporal features for performance improvement."
}
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<abstract>Linguistic ambiguities arising from changes in entities in action flows are a key challenge in instructional cooking videos. In particular, temporally evolving entities present rich and to date understudied challenges for anaphora resolution. For example “oil” mixed with “salt” is later referred to as a “mixture”. In this paper we propose novel annotation guidelines to annotate recipes for the anaphora resolution task, reflecting change in entities. Moreover, we present experimental results for end-to-end multimodal anaphora resolution with the new annotation scheme and propose the use of temporal features for performance improvement.</abstract>
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%0 Conference Proceedings
%T Chop and Change: Anaphora Resolution in Instructional Cooking Videos
%A Oguz, Cennet
%A Kruijff-Korbayova, Ivana
%A Vincent, Emmanuel
%A Denis, Pascal
%A van Genabith, Josef
%Y He, Yulan
%Y Ji, Heng
%Y Li, Sujian
%Y Liu, Yang
%Y Chang, Chua-Hui
%S Findings of the Association for Computational Linguistics: AACL-IJCNLP 2022
%D 2022
%8 November
%I Association for Computational Linguistics
%C Online only
%F oguz-etal-2022-chop
%X Linguistic ambiguities arising from changes in entities in action flows are a key challenge in instructional cooking videos. In particular, temporally evolving entities present rich and to date understudied challenges for anaphora resolution. For example “oil” mixed with “salt” is later referred to as a “mixture”. In this paper we propose novel annotation guidelines to annotate recipes for the anaphora resolution task, reflecting change in entities. Moreover, we present experimental results for end-to-end multimodal anaphora resolution with the new annotation scheme and propose the use of temporal features for performance improvement.
%R 10.18653/v1/2022.findings-aacl.34
%U https://aclanthology.org/2022.findings-aacl.34/
%U https://doi.org/10.18653/v1/2022.findings-aacl.34
%P 364-374
Markdown (Informal)
[Chop and Change: Anaphora Resolution in Instructional Cooking Videos](https://aclanthology.org/2022.findings-aacl.34/) (Oguz et al., Findings 2022)
ACL