@inproceedings{shekhawat-etal-2022-iiserb,
title = "{IISERB} Brains at {S}em{E}val-2022 Task 6: A Deep-learning Framework to Identify Intended Sarcasm in {E}nglish",
author = "Shekhawat, Tanuj and
Kumar, Manoj and
Rathore, Udaybhan and
Joshi, Aditya and
Patro, Jasabanta",
editor = "Emerson, Guy and
Schluter, Natalie and
Stanovsky, Gabriel and
Kumar, Ritesh and
Palmer, Alexis and
Schneider, Nathan and
Singh, Siddharth and
Ratan, Shyam",
booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.semeval-1.131",
doi = "10.18653/v1/2022.semeval-1.131",
pages = "938--944",
abstract = "This paper describes the system architectures and the models submitted by our team {``}IISERB Brains{''} to SemEval 2022 Task 6 competition. We contested for all three sub-tasks floated for the English dataset. On the leader-board, we got 19th rank out of 43 teams for sub-task A, 8th rank out of 22 teams for sub-task B, and 13th rank out of 16 teams for sub-task C. Apart from the submitted results and models, we also report the other models and results that we obtained through our experiments after organizers published the gold labels of their evaluation data. All of our code and links to additional resources are present in GitHub for reproducibility.",
}
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%0 Conference Proceedings
%T IISERB Brains at SemEval-2022 Task 6: A Deep-learning Framework to Identify Intended Sarcasm in English
%A Shekhawat, Tanuj
%A Kumar, Manoj
%A Rathore, Udaybhan
%A Joshi, Aditya
%A Patro, Jasabanta
%Y Emerson, Guy
%Y Schluter, Natalie
%Y Stanovsky, Gabriel
%Y Kumar, Ritesh
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y Singh, Siddharth
%Y Ratan, Shyam
%S Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F shekhawat-etal-2022-iiserb
%X This paper describes the system architectures and the models submitted by our team “IISERB Brains” to SemEval 2022 Task 6 competition. We contested for all three sub-tasks floated for the English dataset. On the leader-board, we got 19th rank out of 43 teams for sub-task A, 8th rank out of 22 teams for sub-task B, and 13th rank out of 16 teams for sub-task C. Apart from the submitted results and models, we also report the other models and results that we obtained through our experiments after organizers published the gold labels of their evaluation data. All of our code and links to additional resources are present in GitHub for reproducibility.
%R 10.18653/v1/2022.semeval-1.131
%U https://aclanthology.org/2022.semeval-1.131
%U https://doi.org/10.18653/v1/2022.semeval-1.131
%P 938-944
Markdown (Informal)
[IISERB Brains at SemEval-2022 Task 6: A Deep-learning Framework to Identify Intended Sarcasm in English](https://aclanthology.org/2022.semeval-1.131) (Shekhawat et al., SemEval 2022)
ACL