4 citations · 8 across the 7 of their papers we have counts for
16 papers
Generalizing over Long Tail Concepts for Medical Term Normalization
Beatrice Portelli, Simone Scaboro, Enrico Santus +3
Medical term normalization consists in mapping a piece of text to a large number of output classes. Given the small size of the annotated datasets and the extremely long tail distr…
AILAB-Udine@SMM4H 22: Limits of Transformers and BERT Ensembles
Beatrice Portelli, Simone Scaboro, Emmanuele Chersoni +2
This paper describes the models developed by the AILAB-Udine team for the SMM4H 22 Shared Task. We explored the limits of Transformer based models on text classification, entity ex…
Increasing Adverse Drug Events extraction robustness on social media: case study on negation and speculation
Simone Scaboro, Beatrice Portelli, Emmanuele Chersoni +2
In the last decade, an increasing number of users have started reporting Adverse Drug Events (ADE) on social media platforms, blogs, and health forums. Given the large volume of re…
Improving Adverse Drug Event Extraction with SpanBERT on Different Text Typologies
Beatrice Portelli, Daniele Passabì, Edoardo Lenzi +3
In recent years, Internet users are reporting Adverse Drug Events (ADE) on social media, blogs and health forums. Because of the large volume of reports, pharmacovigilance is seeki…
A Structured Distributional Model of Sentence Meaning and Processing
Emmanuele Chersoni, Enrico Santus, Ludovica Pannitto +3
Most compositional distributional semantic models represent sentence meaning with a single vector. In this paper, we propose a Structured Distributional Model (SDM) that combines w…
IMaT: Unsupervised Text Attribute Transfer via Iterative Matching and Translation
Zhijing Jin, Di Jin, Jonas Mueller +2
Text attribute transfer aims to automatically rewrite sentences such that they possess certain linguistic attributes, while simultaneously preserving their semantic content. This t…