Fighting the COVID-19 Infodemic with a Holistic BERT Ensemble
This work addresses the spread of misinformation during the COVID-19 pandemic, but it is incremental as it combines existing transformer models without introducing new methods.
The paper tackled the problem of detecting COVID-19 misinformation by developing an ensemble model called TOKOFOU, which achieved an overall F1 score of 89.7% and ranked first in a shared task.
This paper describes the TOKOFOU system, an ensemble model for misinformation detection tasks based on six different transformer-based pre-trained encoders, implemented in the context of the COVID-19 Infodemic Shared Task for English. We fine tune each model on each of the task's questions and aggregate their prediction scores using a majority voting approach. TOKOFOU obtains an overall F1 score of 89.7%, ranking first.