COVID 19 Event Slot

"COVID-19 event slot" research focuses on extracting and classifying information related to COVID-19 events from various data sources, primarily aiming to improve the accuracy and efficiency of information extraction for public health applications. Current research emphasizes the use of large language models, particularly instruction-tuned models, and novel architectures like slot-based attention mechanisms and hierarchical contrastive learning to enhance performance in tasks such as intent classification and slot filling. These advancements are significant for improving the speed and accuracy of analyzing large datasets like social media posts to track the pandemic's evolution and public sentiment, aiding in public health response and resource allocation.