@inproceedings{lee-etal-2023-comparative,
title = "A Comparative Analysis of the Effectiveness of Rare Tokens on Creative Expression using ram{BERT}",
author = "Lee, Youbin and
Kim, Deokgi and
On, Byung-Won and
Lee, Ingyu",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.findings-acl.639",
doi = "10.18653/v1/2023.findings-acl.639",
pages = "10063--10077",
abstract = "Until now, few studies have been explored on Automated Creative Essay Scoring (ACES), in which a pre-trained model automatically labels an essay as a creative or a non-creative. Since the creativity evaluation of essays is very subjective, each evaluator often has his or her own criteria for creativity. For this reason, quantifying creativity in essays is very challenging. In this work, as one of preliminary studies in developing a novel model for ACES, we deeply investigate the correlation between creative essays and expressiveness. Specifically, we explore how rare tokens affect the evaluation of creativity for essays. For such a journey, we present five distinct methods to extract rare tokens, and conduct a comparative study on the correlation between rare tokens and creative essay evaluation results using BERT. Our experimental results showed clear correlation between rare tokens and creative essays. In all test sets, accuracies of our rare token masking-based BERT (ramBERT) model were improved over the existing BERT model up to 14{\%}.",
}
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<abstract>Until now, few studies have been explored on Automated Creative Essay Scoring (ACES), in which a pre-trained model automatically labels an essay as a creative or a non-creative. Since the creativity evaluation of essays is very subjective, each evaluator often has his or her own criteria for creativity. For this reason, quantifying creativity in essays is very challenging. In this work, as one of preliminary studies in developing a novel model for ACES, we deeply investigate the correlation between creative essays and expressiveness. Specifically, we explore how rare tokens affect the evaluation of creativity for essays. For such a journey, we present five distinct methods to extract rare tokens, and conduct a comparative study on the correlation between rare tokens and creative essay evaluation results using BERT. Our experimental results showed clear correlation between rare tokens and creative essays. In all test sets, accuracies of our rare token masking-based BERT (ramBERT) model were improved over the existing BERT model up to 14%.</abstract>
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%0 Conference Proceedings
%T A Comparative Analysis of the Effectiveness of Rare Tokens on Creative Expression using ramBERT
%A Lee, Youbin
%A Kim, Deokgi
%A On, Byung-Won
%A Lee, Ingyu
%Y Rogers, Anna
%Y Boyd-Graber, Jordan
%Y Okazaki, Naoaki
%S Findings of the Association for Computational Linguistics: ACL 2023
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F lee-etal-2023-comparative
%X Until now, few studies have been explored on Automated Creative Essay Scoring (ACES), in which a pre-trained model automatically labels an essay as a creative or a non-creative. Since the creativity evaluation of essays is very subjective, each evaluator often has his or her own criteria for creativity. For this reason, quantifying creativity in essays is very challenging. In this work, as one of preliminary studies in developing a novel model for ACES, we deeply investigate the correlation between creative essays and expressiveness. Specifically, we explore how rare tokens affect the evaluation of creativity for essays. For such a journey, we present five distinct methods to extract rare tokens, and conduct a comparative study on the correlation between rare tokens and creative essay evaluation results using BERT. Our experimental results showed clear correlation between rare tokens and creative essays. In all test sets, accuracies of our rare token masking-based BERT (ramBERT) model were improved over the existing BERT model up to 14%.
%R 10.18653/v1/2023.findings-acl.639
%U https://aclanthology.org/2023.findings-acl.639
%U https://doi.org/10.18653/v1/2023.findings-acl.639
%P 10063-10077
Markdown (Informal)
[A Comparative Analysis of the Effectiveness of Rare Tokens on Creative Expression using ramBERT](https://aclanthology.org/2023.findings-acl.639) (Lee et al., Findings 2023)
ACL