77 citations · 87 across the 5 of their papers we have counts for
6 papers
Evaluation of ChatGPT Family of Models for Biomedical Reasoning and Classification
Shan Chen, Yingya Li, Sheng Lu +4
Recent advances in large language models (LLMs) have shown impressive ability in biomedical question-answering, but have not been adequately investigated for more specific biomedic…
Mitigating Data Scarcity for Large Language Models
Hoang Van
In recent years, pretrained neural language models (PNLMs) have taken the field of natural language processing by storm, achieving new benchmarks and state-of-the-art performances.…
How May I Help You? Using Neural Text Simplification to Improve Downstream NLP Tasks
Hoang Van, Zheng Tang, Mihai Surdeanu
The general goal of text simplification (TS) is to reduce text complexity for human consumption. This paper investigates another potential use of neural TS: assisting machines perf…
Cheap and Good? Simple and Effective Data Augmentation for Low Resource Machine Reading
Hoang Van, Vikas Yadav, Mihai Surdeanu
We propose a simple and effective strategy for data augmentation for low-resource machine reading comprehension (MRC). Our approach first pretrains the answer extraction components…
AutoMeTS: The Autocomplete for Medical Text Simplification
Hoang Van, David Kauchak, Gondy Leroy
The goal of text simplification (TS) is to transform difficult text into a version that is easier to understand and more broadly accessible to a wide variety of readers. In some do…
The Language of Food during the Pandemic: Hints about the Dietary Effects of Covid-19
Hoang Van, Ahmad Musa, Mihai Surdeanu +1
We study the language of food on Twitter during the pandemic lockdown in the United States, focusing on the two month period of March 15 to May 15, 2020. Specifically, we analyze o…