@inproceedings{basu-roy-chowdhury-etal-2021-everything,
title = "Is Everything in Order? A Simple Way to Order Sentences",
author = "Basu Roy Chowdhury, Somnath and
Brahman, Faeze and
Chaturvedi, Snigdha",
editor = "Moens, Marie-Francine and
Huang, Xuanjing and
Specia, Lucia and
Yih, Scott Wen-tau",
booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2021",
address = "Online and Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.emnlp-main.841",
doi = "10.18653/v1/2021.emnlp-main.841",
pages = "10769--10779",
abstract = "The task of organizing a shuffled set of sentences into a coherent text has been used to evaluate a machine{'}s understanding of causal and temporal relations. We formulate the sentence ordering task as a conditional text-to-marker generation problem. We present Reorder-BART (Re-BART) that leverages a pre-trained Transformer-based model to identify a coherent order for a given set of shuffled sentences. The model takes a set of shuffled sentences with sentence-specific markers as input and generates a sequence of position markers of the sentences in the ordered text. Re-BART achieves the state-of-the-art performance across 7 datasets in Perfect Match Ratio (PMR) and Kendall{'}s tau. We perform evaluations in a zero-shot setting, showcasing that our model is able to generalize well across other datasets. We additionally perform several experiments to understand the functioning and limitations of our framework.",
}
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<abstract>The task of organizing a shuffled set of sentences into a coherent text has been used to evaluate a machine’s understanding of causal and temporal relations. We formulate the sentence ordering task as a conditional text-to-marker generation problem. We present Reorder-BART (Re-BART) that leverages a pre-trained Transformer-based model to identify a coherent order for a given set of shuffled sentences. The model takes a set of shuffled sentences with sentence-specific markers as input and generates a sequence of position markers of the sentences in the ordered text. Re-BART achieves the state-of-the-art performance across 7 datasets in Perfect Match Ratio (PMR) and Kendall’s tau. We perform evaluations in a zero-shot setting, showcasing that our model is able to generalize well across other datasets. We additionally perform several experiments to understand the functioning and limitations of our framework.</abstract>
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%0 Conference Proceedings
%T Is Everything in Order? A Simple Way to Order Sentences
%A Basu Roy Chowdhury, Somnath
%A Brahman, Faeze
%A Chaturvedi, Snigdha
%Y Moens, Marie-Francine
%Y Huang, Xuanjing
%Y Specia, Lucia
%Y Yih, Scott Wen-tau
%S Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
%D 2021
%8 November
%I Association for Computational Linguistics
%C Online and Punta Cana, Dominican Republic
%F basu-roy-chowdhury-etal-2021-everything
%X The task of organizing a shuffled set of sentences into a coherent text has been used to evaluate a machine’s understanding of causal and temporal relations. We formulate the sentence ordering task as a conditional text-to-marker generation problem. We present Reorder-BART (Re-BART) that leverages a pre-trained Transformer-based model to identify a coherent order for a given set of shuffled sentences. The model takes a set of shuffled sentences with sentence-specific markers as input and generates a sequence of position markers of the sentences in the ordered text. Re-BART achieves the state-of-the-art performance across 7 datasets in Perfect Match Ratio (PMR) and Kendall’s tau. We perform evaluations in a zero-shot setting, showcasing that our model is able to generalize well across other datasets. We additionally perform several experiments to understand the functioning and limitations of our framework.
%R 10.18653/v1/2021.emnlp-main.841
%U https://aclanthology.org/2021.emnlp-main.841
%U https://doi.org/10.18653/v1/2021.emnlp-main.841
%P 10769-10779
Markdown (Informal)
[Is Everything in Order? A Simple Way to Order Sentences](https://aclanthology.org/2021.emnlp-main.841) (Basu Roy Chowdhury et al., EMNLP 2021)
ACL
- Somnath Basu Roy Chowdhury, Faeze Brahman, and Snigdha Chaturvedi. 2021. Is Everything in Order? A Simple Way to Order Sentences. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 10769–10779, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.