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Found 8 papers, 6 papers with code
Evaluation of ChatGPT Family of Models for Biomedical Reasoning and Classification
The first task is classifying whether statements of clinical and policy recommendations in scientific literature constitute health advice.
Mitigating Data Scarcity for Large Language Models
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.
Extracting Space Situational Awareness Events from News Text
Space situational awareness typically makes use of physical measurements from radar, telescopes, and other assets to monitor satellites and other spacecraft for operational, navigational, and defense purposes.
How May I Help You? Using Neural Text Simplification to Improve Downstream NLP Tasks
The general goal of text simplification (TS) is to reduce text complexity for human consumption.
Cheap and Good? Simple and Effective Data Augmentation for Low Resource Machine Reading
We propose a simple and effective strategy for data augmentation for low-resource machine reading comprehension (MRC).
AutoMeTS: The Autocomplete for Medical Text Simplification
In this paper, we examine the application of autocomplete to text simplification in the medical domain.
The Language of Food during the Pandemic: Hints about the Dietary Effects of Covid-19
Specifically, we analyze over770, 000 tweets published during the lockdown and the equivalent period in the five previous years and highlight several worrying trends.
What does the language of foods say about us?
Second, we investigate the effect of socioeconomic factors (income, poverty, and education) on predicting state-level T2DM rates.
