SPEED++: A Multilingual Event Extraction Framework for Epidemic Prediction and Preparedness
Tanmay Parekh, Jeffrey Kwan, Jiarui Yu, Sparsh Johri, Hyosang Ahn, Sreya Muppalla, Kai-Wei Chang, Wei Wang, and Nanyun Peng, in Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.
Abstract
We introduce SPEED++, the first multilingual Event Extraction framework for extracting epidemic-related information from social media. Our framework is capable of providing epidemic warnings in diverse languages and demonstrates the efficacy of zero-shot cross-lingual models trained on English data for extracting information relevant to various diseases.
Bib Entry
@inproceedings{parekh2024speed,
title = {SPEED++: A Multilingual Event Extraction Framework for Epidemic Prediction and Preparedness},
author = {Parekh, Tanmay and Kwan, Jeffrey and Yu, Jiarui and Johri, Sparsh and Ahn, Hyosang and Muppalla, Sreya and Chang, Kai-Wei and Wang, Wei and Peng, Nanyun},
booktitle = {Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
year = {2024}
}