@inproceedings{li-etal-2023-ecnu,
title = "{ECNU}{\_}{MIV} at {S}em{E}val-2023 Task 1: {CTIM} - Contrastive Text-Image Model for Multilingual Visual Word Sense Disambiguation",
author = "Li, Zhenghui and
Zhang, Qi and
Xia, Xueyin and
Ye, Yinxiang and
Zhang, Qi and
Huang, Cong",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Da San Martino, Giovanni and
Tayyar Madabushi, Harish and
Kumar, Ritesh and
Sartori, Elisa},
booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.semeval-1.13",
doi = "10.18653/v1/2023.semeval-1.13",
pages = "101--107",
abstract = "Our team focuses on the multimodal domain of images and texts, we propose a model that can learn the matching relationship between text-image pairs by contrastive learning. More specifically, We train the model from the labeled data provided by the official organizer, after pre-training, texts are used to reference learned visual concepts enabling visual word sense disambiguation tasks. In addition, the top results our teams get have been released showing the effectiveness of our solution.",
}
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%0 Conference Proceedings
%T ECNU_MIV at SemEval-2023 Task 1: CTIM - Contrastive Text-Image Model for Multilingual Visual Word Sense Disambiguation
%A Li, Zhenghui
%A Zhang, Qi
%A Xia, Xueyin
%A Ye, Yinxiang
%A Huang, Cong
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Da San Martino, Giovanni
%Y Tayyar Madabushi, Harish
%Y Kumar, Ritesh
%Y Sartori, Elisa
%S Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F li-etal-2023-ecnu
%X Our team focuses on the multimodal domain of images and texts, we propose a model that can learn the matching relationship between text-image pairs by contrastive learning. More specifically, We train the model from the labeled data provided by the official organizer, after pre-training, texts are used to reference learned visual concepts enabling visual word sense disambiguation tasks. In addition, the top results our teams get have been released showing the effectiveness of our solution.
%R 10.18653/v1/2023.semeval-1.13
%U https://aclanthology.org/2023.semeval-1.13
%U https://doi.org/10.18653/v1/2023.semeval-1.13
%P 101-107
Markdown (Informal)
[ECNU_MIV at SemEval-2023 Task 1: CTIM - Contrastive Text-Image Model for Multilingual Visual Word Sense Disambiguation](https://aclanthology.org/2023.semeval-1.13) (Li et al., SemEval 2023)
ACL