3 citations · 11 across the 5 of their papers we have counts for
6 papers · 1 filter
ReLay: Personalized LLM-Generated Plain-Language Summaries for Better Understanding, but at What Cost?
Joey Chan, Yikun Han, Jingyuan Chen +8
Plain Language Summaries (PLS) aim to make research accessible to lay readers, but they are typically written in a one-size-fits-all style that ignores differences in readers' info…
Are LLM-generated plain language summaries truly understandable? A large-scale crowdsourced evaluation
Yue Guo, Jae Ho Sohn, Gondy Leroy +1
Plain language summaries (PLSs) are essential for facilitating effective communication between clinicians and patients by making complex medical information easier for laypeople to…
Personalized Jargon Identification for Enhanced Interdisciplinary Communication
Yue Guo, Joseph Chee Chang, Maria Antoniak +4
Scientific jargon can impede researchers when they read materials from other domains. Current methods of jargon identification mainly use corpus-level familiarity indicators (e.g.,…
APPLS: Evaluating Evaluation Metrics for Plain Language Summarization
Yue Guo, Tal August, Gondy Leroy +2
While there has been significant development of models for Plain Language Summarization (PLS), evaluation remains a challenge. PLS lacks a dedicated assessment metric, and the suit…
Retrieval augmentation of large language models for lay language generation
Yue Guo, Wei Qiu, Gondy Leroy +2
Recent lay language generation systems have used Transformer models trained on a parallel corpus to increase health information accessibility. However, the applicability of these m…
Automated Lay Language Summarization of Biomedical Scientific Reviews
Yue Guo, Wei Qiu, Yizhong Wang +1
Health literacy has emerged as a crucial factor in making appropriate health decisions and ensuring treatment outcomes. However, medical jargon and the complex structure of profess…