activity
20182020
most citedAutomatic Text Summarization of COVID-19 Medical Research Articles using BERT and GPT-2

82 citations · 170 across the 4 of their papers we have counts for

collaborators

8 papers

cs.CL2020

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…

cs.CL202010 cited

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…

cs.CL202082 cited

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…

cs.CL2020

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…

cs.LG201971 cited

Learning Data Manipulation for Augmentation and Weighting

Zhiting Hu, Bowen Tan, Ruslan Salakhutdinov +2

Manipulating data, such as weighting data examples or augmenting with new instances, has been increasingly used to improve model training. Previous work has studied various rule- o…

cs.CL20197 cited

AgentGraph: Towards Universal Dialogue Management with Structured Deep Reinforcement Learning

Lu Chen, Zhi Chen, Bowen Tan +3

Dialogue policy plays an important role in task-oriented spoken dialogue systems. It determines how to respond to users. The recently proposed deep reinforcement learning (DRL) app…