@inproceedings{swamy-etal-2020-nit,
title = "{NIT}-Agartala-{NLP}-Team at {S}em{E}val-2020 Task 8: Building Multimodal Classifiers to Tackle {I}nternet Humor",
author = "Swamy, Steve Durairaj and
Laddha, Shubham and
Abdussalam, Basil and
Datta, Debayan and
Jamatia, Anupam",
editor = "Herbelot, Aurelie and
Zhu, Xiaodan and
Palmer, Alexis and
Schneider, Nathan and
May, Jonathan and
Shutova, Ekaterina",
booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
month = dec,
year = "2020",
address = "Barcelona (online)",
publisher = "International Committee for Computational Linguistics",
url = "https://aclanthology.org/2020.semeval-1.156",
doi = "10.18653/v1/2020.semeval-1.156",
pages = "1179--1189",
abstract = "The paper describes the systems submitted to SemEval-2020 Task 8: Memotion by the {`}NIT-Agartala-NLP-Team{'}. A dataset of 8879 memes was made available by the task organizers to train and test our models. Our systems include a Logistic Regression baseline, a BiLSTM +Attention-based learner and a transfer learning approach with BERT. For the three sub-tasks A, B and C, we attained ranks 24/33, 11/29 and 15/26, respectively. We highlight our difficulties in harnessing image information as well as some techniques and handcrafted features we employ to overcome these issues. We also discuss various modelling issues and theorize possible solutions and reasons as to why these problems persist.",
}
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%0 Conference Proceedings
%T NIT-Agartala-NLP-Team at SemEval-2020 Task 8: Building Multimodal Classifiers to Tackle Internet Humor
%A Swamy, Steve Durairaj
%A Laddha, Shubham
%A Abdussalam, Basil
%A Datta, Debayan
%A Jamatia, Anupam
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F swamy-etal-2020-nit
%X The paper describes the systems submitted to SemEval-2020 Task 8: Memotion by the ‘NIT-Agartala-NLP-Team’. A dataset of 8879 memes was made available by the task organizers to train and test our models. Our systems include a Logistic Regression baseline, a BiLSTM +Attention-based learner and a transfer learning approach with BERT. For the three sub-tasks A, B and C, we attained ranks 24/33, 11/29 and 15/26, respectively. We highlight our difficulties in harnessing image information as well as some techniques and handcrafted features we employ to overcome these issues. We also discuss various modelling issues and theorize possible solutions and reasons as to why these problems persist.
%R 10.18653/v1/2020.semeval-1.156
%U https://aclanthology.org/2020.semeval-1.156
%U https://doi.org/10.18653/v1/2020.semeval-1.156
%P 1179-1189
Markdown (Informal)
[NIT-Agartala-NLP-Team at SemEval-2020 Task 8: Building Multimodal Classifiers to Tackle Internet Humor](https://aclanthology.org/2020.semeval-1.156) (Swamy et al., SemEval 2020)
ACL