@inproceedings{sharma-etal-2023-billy,
title = "Billy-Batson at {S}em{E}val-2023 Task 5: An Information Condensation based System for Clickbait Spoiling",
author = "Sharma, Anubhav and
Joshi, Sagar and
Abhishek, Tushar and
Mamidi, Radhika and
Varma, Vasudeva",
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-1.259",
doi = "10.18653/v1/2023.semeval-1.259",
pages = "1878--1889",
abstract = "The Clickbait Challenge targets spoiling the clickbaits using short pieces of information known as spoilers to satisfy the curiosity induced by a clickbait post. The large context of the article associated with the clickbait and differences in the spoiler forms, make the task challenging. Hence, to tackle the large context, we propose an Information Condensation-based approach, which prunes down the unnecessary context. Given an article, our filtering module optimised with a contrastive learning objective first selects the parapraphs that are the most relevant to the corresponding clickbait.The resulting condensed article is then fed to the two downstream tasks of spoiler type classification and spoiler generation. We demonstrate and analyze the gains from this approach on both the tasks. Overall, we win the task of spoiler type classification and achieve competitive results on spoiler generation.",
}
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<abstract>The Clickbait Challenge targets spoiling the clickbaits using short pieces of information known as spoilers to satisfy the curiosity induced by a clickbait post. The large context of the article associated with the clickbait and differences in the spoiler forms, make the task challenging. Hence, to tackle the large context, we propose an Information Condensation-based approach, which prunes down the unnecessary context. Given an article, our filtering module optimised with a contrastive learning objective first selects the parapraphs that are the most relevant to the corresponding clickbait.The resulting condensed article is then fed to the two downstream tasks of spoiler type classification and spoiler generation. We demonstrate and analyze the gains from this approach on both the tasks. Overall, we win the task of spoiler type classification and achieve competitive results on spoiler generation.</abstract>
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%0 Conference Proceedings
%T Billy-Batson at SemEval-2023 Task 5: An Information Condensation based System for Clickbait Spoiling
%A Sharma, Anubhav
%A Joshi, Sagar
%A Abhishek, Tushar
%A Mamidi, Radhika
%A Varma, Vasudeva
%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 sharma-etal-2023-billy
%X The Clickbait Challenge targets spoiling the clickbaits using short pieces of information known as spoilers to satisfy the curiosity induced by a clickbait post. The large context of the article associated with the clickbait and differences in the spoiler forms, make the task challenging. Hence, to tackle the large context, we propose an Information Condensation-based approach, which prunes down the unnecessary context. Given an article, our filtering module optimised with a contrastive learning objective first selects the parapraphs that are the most relevant to the corresponding clickbait.The resulting condensed article is then fed to the two downstream tasks of spoiler type classification and spoiler generation. We demonstrate and analyze the gains from this approach on both the tasks. Overall, we win the task of spoiler type classification and achieve competitive results on spoiler generation.
%R 10.18653/v1/2023.semeval-1.259
%U https://aclanthology.org/2023.semeval-1.259
%U https://doi.org/10.18653/v1/2023.semeval-1.259
%P 1878-1889
Markdown (Informal)
[Billy-Batson at SemEval-2023 Task 5: An Information Condensation based System for Clickbait Spoiling](https://aclanthology.org/2023.semeval-1.259) (Sharma et al., SemEval 2023)
ACL