Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/172421
Title: Expertise Style Transfer: A New Task Towards Better Communication between Experts and Laymen
Authors: Yixin Cao 
Ruihao Shui
Liangming Pan
Min-Yen Kan 
Zhiyuan Liu
Tat-Seng Chua 
Issue Date: 2020
Citation: Yixin Cao, Ruihao Shui, Liangming Pan, Min-Yen Kan, Zhiyuan Liu, Tat-Seng Chua (2020). Expertise Style Transfer: A New Task Towards Better Communication between Experts and Laymen. Proceedings of the 2020 Annual Meeting of the Association of Computational Linguistics (ACL '20) : 1-11. ScholarBank@NUS Repository.
Abstract: The curse of knowledge can impede communication between experts and laymen. We propose a new task of expertise style transfer and contribute a manually annotated dataset with the goal of alleviating such cognitive biases. Solving this task not only simplifies the professional language, but also improves the accuracy and expertise level of laymen descriptions using simple words. This is a challenging task, unaddressed in previous work, as it requires the models to have expert intelligence in order to modify text with a deep understanding of domain knowledge and structures. We establish the benchmark performance of five stateof-the-art models for style transfer and text simplification. The results demonstrate a significant gap between machine and human performance. We also discuss the challenges of automatic evaluation, to provide insights into future research directions. The dataset is publicly available at https://srhthu.github. io/expertise-style-transfer/.
Source Title: Proceedings of the 2020 Annual Meeting of the Association of Computational Linguistics (ACL '20)
URI: https://scholarbank.nus.edu.sg/handle/10635/172421
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