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        <title>LMML at SemEval-2020 Task 7: Siamese Transformers for Rating Humor in Edited News Headlines</title>
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        <namePart type="given">Pramodith</namePart>
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    <abstract>This paper contains a description of my solution to the problem statement of SemEval 2020: Assessing the Funniness of Edited News Headlines. I propose a Siamese Transformer based approach, coupled with a Global Attention mechanism that makes use of contextual embeddings and focus words, to generate important features that are fed to a 2 layer perceptron to rate the funniness of the edited headline. I detail various experiments to show the performance of the system. The proposed approach outperforms a baseline Bi-LSTM architecture and finished 5th (out of 49 teams) in sub-task 1 and 4th (out of 32 teams) in sub-task 2 of the competition and was the best non-ensemble model in both tasks.</abstract>
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%0 Conference Proceedings
%T LMML at SemEval-2020 Task 7: Siamese Transformers for Rating Humor in Edited News Headlines
%A Ballapuram, Pramodith
%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 ballapuram-2020-lmml
%X This paper contains a description of my solution to the problem statement of SemEval 2020: Assessing the Funniness of Edited News Headlines. I propose a Siamese Transformer based approach, coupled with a Global Attention mechanism that makes use of contextual embeddings and focus words, to generate important features that are fed to a 2 layer perceptron to rate the funniness of the edited headline. I detail various experiments to show the performance of the system. The proposed approach outperforms a baseline Bi-LSTM architecture and finished 5th (out of 49 teams) in sub-task 1 and 4th (out of 32 teams) in sub-task 2 of the competition and was the best non-ensemble model in both tasks.
%R 10.18653/v1/2020.semeval-1.134
%U https://aclanthology.org/2020.semeval-1.134/
%U https://doi.org/10.18653/v1/2020.semeval-1.134
%P 1026-1032

Markdown (Informal)

[LMML at SemEval-2020 Task 7: Siamese Transformers for Rating Humor in Edited News Headlines](https://aclanthology.org/2020.semeval-1.134/) (Ballapuram, SemEval 2020)

• LMML at SemEval-2020 Task 7: Siamese Transformers for Rating Humor in Edited News Headlines (Ballapuram, SemEval 2020)

ACL

• Pramodith Ballapuram. 2020. LMML at SemEval-2020 Task 7: Siamese Transformers for Rating Humor in Edited News Headlines. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1026–1032, Barcelona (online). International Committee for Computational Linguistics.