@inproceedings{yuan-etal-2020-one,
title = "One Size Does Not Fit All: Generating and Evaluating Variable Number of Keyphrases",
author = "Yuan, Xingdi and
Wang, Tong and
Meng, Rui and
Thaker, Khushboo and
Brusilovsky, Peter and
He, Daqing and
Trischler, Adam",
editor = "Jurafsky, Dan and
Chai, Joyce and
Schluter, Natalie and
Tetreault, Joel",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.acl-main.710",
doi = "10.18653/v1/2020.acl-main.710",
pages = "7961--7975",
abstract = "Different texts shall by nature correspond to different number of keyphrases. This desideratum is largely missing from existing neural keyphrase generation models. In this study, we address this problem from both modeling and evaluation perspectives. We first propose a recurrent generative model that generates multiple keyphrases as delimiter-separated sequences. Generation diversity is further enhanced with two novel techniques by manipulating decoder hidden states. In contrast to previous approaches, our model is capable of generating diverse keyphrases and controlling number of outputs. We further propose two evaluation metrics tailored towards the variable-number generation. We also introduce a new dataset StackEx that expands beyond the only existing genre (i.e., academic writing) in keyphrase generation tasks. With both previous and new evaluation metrics, our model outperforms strong baselines on all datasets.",
}
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<abstract>Different texts shall by nature correspond to different number of keyphrases. This desideratum is largely missing from existing neural keyphrase generation models. In this study, we address this problem from both modeling and evaluation perspectives. We first propose a recurrent generative model that generates multiple keyphrases as delimiter-separated sequences. Generation diversity is further enhanced with two novel techniques by manipulating decoder hidden states. In contrast to previous approaches, our model is capable of generating diverse keyphrases and controlling number of outputs. We further propose two evaluation metrics tailored towards the variable-number generation. We also introduce a new dataset StackEx that expands beyond the only existing genre (i.e., academic writing) in keyphrase generation tasks. With both previous and new evaluation metrics, our model outperforms strong baselines on all datasets.</abstract>
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%0 Conference Proceedings
%T One Size Does Not Fit All: Generating and Evaluating Variable Number of Keyphrases
%A Yuan, Xingdi
%A Wang, Tong
%A Meng, Rui
%A Thaker, Khushboo
%A Brusilovsky, Peter
%A He, Daqing
%A Trischler, Adam
%Y Jurafsky, Dan
%Y Chai, Joyce
%Y Schluter, Natalie
%Y Tetreault, Joel
%S Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F yuan-etal-2020-one
%X Different texts shall by nature correspond to different number of keyphrases. This desideratum is largely missing from existing neural keyphrase generation models. In this study, we address this problem from both modeling and evaluation perspectives. We first propose a recurrent generative model that generates multiple keyphrases as delimiter-separated sequences. Generation diversity is further enhanced with two novel techniques by manipulating decoder hidden states. In contrast to previous approaches, our model is capable of generating diverse keyphrases and controlling number of outputs. We further propose two evaluation metrics tailored towards the variable-number generation. We also introduce a new dataset StackEx that expands beyond the only existing genre (i.e., academic writing) in keyphrase generation tasks. With both previous and new evaluation metrics, our model outperforms strong baselines on all datasets.
%R 10.18653/v1/2020.acl-main.710
%U https://aclanthology.org/2020.acl-main.710
%U https://doi.org/10.18653/v1/2020.acl-main.710
%P 7961-7975
Markdown (Informal)
[One Size Does Not Fit All: Generating and Evaluating Variable Number of Keyphrases](https://aclanthology.org/2020.acl-main.710) (Yuan et al., ACL 2020)
ACL