Expertise Style Transfer: A New Task Towards Better Communication between Experts and Laymen

38237

Authors

nan

Abstract

AbstractThe 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 state-of-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/.

Keywords

nan

Full Content

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 1061–1071 July 5 - 10, 2020. c⃝2020 Association for Computational Linguistics 1061 Expertise Style Transfer: A New Task Towards Better Communication between Experts and Laymen Yixin Cao1 Ruihao Shui21 Liangming Pan21 Min-Yen Kan1 Zhiyuan Liu3 Tat-Seng Chua1 1School of Computing, National University of Singapore, Singapore 2NUS Graduate School for Integrative Sciences and Engineering 3Department of CST, Tsinghua University, Beijing, China caoyixin2011@gmail.com, {ruihaoshui,e0272310}@u.nus.edu liuzy@tsinghua.edu.cn, {kanmy@comp.,dcscts@}nus.edu.sg Abstract The curse of knowledge can impede commu- nication between experts and laymen. We pro- pose 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 pro- fessional language, but also improves the accu- racy 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 estab- lish the benchmark performance of five state- of-the-art models for style transfer and text simplification. The results demonstrate a sig- nificant gap between machine and human per- formance. We also discuss the challenges of automatic evaluation, to provide insights into future research directions. The dataset is pub- licly available at https://srhthu.github. io/expertise-style-transfer/. 1 Introduction The curse of knowledge (Camerer et al., 1989) is a pervasive cognitive bias exhibited across all do- mains, leading to discrepancies between an expert’s advice and a layman’s understanding of it (Tan and Goonawardene, 2017). Take medical consultations as an example: patients often find it difficult to un- derstand their doctors’ language. On the other hand, it is important for doctors to accurately disclose the exact illness conditions based on patients’ simple vocabulary. Misunderstanding may lead to failures in diagnosis and prompt treatment, or even death. How to automatically adjust the expertise level of texts is critical for effective communication. In this paper, we propose a new task of text style transfer between expert language and layman lan- guage, namely Expertise Style Transfer, and con- tribute a manually annotated dataset in the medical Many cause dyspnea, pleuritic chest pain, or both. The most common symptoms, regardless of the type of fluid in the pleural space or its cause, are shortness of breath and chest pain. About 1/1000 hypertensive patients has a pheochromocytoma. The incidence of Pheochromocytomas may be quite small. The lesion slowly enlarges, often ulcerates, and spread to other skin areas. Lesions heal slowly, with scarring. The sores slowly enlarge and spread to nearby tissue, causing further damage. Sores heal slowly and may result in permanent scarring. In patients with papilledema, vision is usually not affected initially, but seconds-long graying out of vision, flickering, or blurred or double vision may occur. At first, papilledema may be present without affecting vision. Fleeting vision changes (blurred vision, double vision, flickering, or complete loss of vision) typically lasting seconds are characteristic of papilledema. Figure 1: …

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Labeled Text

AbstractThe 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 state-of-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

Publication Details

Paper ID:
38237
Year:
2020
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan