82 citations · 266 across the 17 of their papers we have counts for
4 papers · 1 filter
Summarizing Text on Any Aspects: A Knowledge-Informed Weakly-Supervised Approach
Bowen Tan, Lianhui Qin, Eric P. Xing +1
Given a document and a target aspect (e.g., a topic of interest), aspect-based abstractive summarization attempts to generate a summary with respect to the aspect. Previous studies…
On the Generation of Medical Dialogues for COVID-19
Wenmian Yang, Guangtao Zeng, Bowen Tan +9
Under the pandemic of COVID-19, people experiencing COVID19-related symptoms or exposed to risk factors have a pressing need to consult doctors. Due to hospital closure, a lot of c…
Automatic Text Summarization of COVID-19 Medical Research Articles using BERT and GPT-2
Virapat Kieuvongngam, Bowen Tan, Yiming Niu
With the COVID-19 pandemic, there is a growing urgency for medical community to keep up with the accelerating growth in the new coronavirus-related literature. As a result, the COV…
Progressive Generation of Long Text with Pretrained Language Models
Bowen Tan, Zichao Yang, Maruan AI-Shedivat +2
Large-scale language models (LMs) pretrained on massive corpora of text, such as GPT-2, are powerful open-domain text generators. However, as our systematic examination reveals, it…