Papers by Edoardo Lenzi
BERT Prescriptions to Avoid Unwanted Headaches: A Comparison of Transformer Architectures for Adverse Drug Event Detection (2021.eacl-main)
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| Challenge: | Pretrained transformer-based models are a common choice for identifying drug events from social media texts. |
| Approach: | They propose to compare transformer-based models with in-domain language pretraining to find out which one is better at ADE detection. |
| Outcome: | The proposed models outperform SpanBERT and PubMedBERT on two benchmarks. |