Different from general documents, it is recognised that the ease with which
people can understand a biomedical text is eminently varied, owing to the
highly technical nature of biomedical documents and the variance of readers'
domain knowledge. However, existing biomedical document summarization systems
have paid little attention to readability control, leaving users with summaries
that are incompatible with their levels of expertise. In recognition of this
urgent demand, we introduce a new task of readability controllable
summarization for biomedical documents, which aims to recognise users'
readability demands and generate summaries that better suit their needs:
technical summaries for experts and plain language summaries (PLS) for laymen.
To establish this task, we construct a corpus consisting of biomedical papers
with technical summaries and PLSs written by the authors, and benchmark
multiple advanced controllable abstractive and extractive summarization models
based on pre-trained language models (PLMs) with prevalent controlling and
generation techniques. Moreover, we propose a novel masked language model (MLM)
based metric and its variant to effectively evaluate the readability
discrepancy between lay and technical summaries. Experimental results from
automated and human evaluations show that though current control techniques
allow for a certain degree of readability adjustment during generation, the
performance of existing controllable summarization methods is far from
desirable in this task.

本文介绍了一种针对生物医学文本的可读性控制式摘要方法，可生成专家和非专业人士阅读所需的技术和简易语言摘要，并以生物医学论文为例进行了实验验证和比较。

可控可读性生物医学文档摘要

Readability Controllable Biomedical Document Summarization

When seeking information not covered in patient-friendly documents, like
medical pamphlets, healthcare consumers may turn to the research literature.
Reading medical papers, however, can be a challenging experience. To improve
access to medical papers, we introduce a novel interactive interface-Paper
Plain-with four features powered by natural language processing: definitions of
unfamiliar terms, in-situ plain language section summaries, a collection of key
questions that guide readers to answering passages, and plain language
summaries of the answering passages. We evaluate Paper Plain, finding that
participants who use Paper Plain have an easier time reading and understanding
research papers without a loss in paper comprehension compared to those who use
a typical PDF reader. Altogether, the study results suggest that guiding
readers to relevant passages and providing plain language summaries, or
"gists," alongside the original paper content can make reading medical papers
easier and give readers more confidence to approach these papers.

通过自然语言处理，介绍了一种新的交互式界面 Paper Plain，该界面包含四个功能，可为医学文献的阅读提供完善的辅助功能，包括生词释义、平易近人的章节概括以及相关问题，研究表明使用 Paper Plain 的参与者在阅读和理解医学文献方面相比于传统格式的 PDF 阅读器有更容易的体验而且不会降低理解难度，该研究成果表明，向读者提供相关章节引导并提供医学文献的中英文互译摘要可以使得阅读医学文献更加轻松，鼓励读者更多地接触这些文献。