no code implementations • EMNLP (sustainlp) 2020 • Giuseppe Lancioni, Saida S.Mohamed, Beatrice Portelli, Giuseppe Serra, Carlo Tasso
Keyphrase Generation is the task of predicting Keyphrases (KPs), short phrases that summarize the semantic meaning of a given document.
no code implementations • SMM4H (COLING) 2022 • Beatrice Portelli, Simone Scaboro, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra
This paper describes the models developed by the AILAB-Udine team for the SMM4H’22 Shared Task.
no code implementations • 31 Jul 2023 • François Remy, Simone Scaboro, Beatrice Portelli
Biomedical entity linking, also known as biomedical concept normalization, has recently witnessed the rise to prominence of zero-shot contrastive models.
1 code implementation • 21 Oct 2022 • Beatrice Portelli, Simone Scaboro, Enrico Santus, Hooman Sedghamiz, Emmanuele Chersoni, Giuseppe Serra
Medical term normalization consists in mapping a piece of text to a large number of output classes.
no code implementations • 7 Sep 2022 • Beatrice Portelli, Simone Scaboro, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra
This paper describes the models developed by the AILAB-Udine team for the SMM4H 22 Shared Task.
no code implementations • 6 Sep 2022 • Simone Scaboro, Beatrice Portelli, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra
In the last decade, an increasing number of users have started reporting Adverse Drug Events (ADE) on social media platforms, blogs, and health forums.
1 code implementation • WNUT (ACL) 2021 • Simone Scaboro, Beatrice Portelli, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra
Adverse Drug Event (ADE) extraction models can rapidly examine large collections of social media texts, detecting mentions of drug-related adverse reactions and trigger medical investigations.
1 code implementation • 25 Jul 2021 • Kevin Roitero, Michael Soprano, Beatrice Portelli, Massimiliano De Luise, Damiano Spina, Vincenzo Della Mea, Giuseppe Serra, Stefano Mizzaro, Gianluca Demartini
Our results show that: workers are able to detect and objectively categorize online (mis)information related to COVID-19; both crowdsourced and expert judgments can be transformed and aggregated to improve quality; worker background and other signals (e. g., source of information, behavior) impact the quality of the data.
1 code implementation • 19 May 2021 • Beatrice Portelli, Daniele Passabì, Edoardo Lenzi, Giuseppe Serra, Enrico Santus, Emmanuele Chersoni
In recent years, Internet users are reporting Adverse Drug Events (ADE) on social media, blogs and health forums.
1 code implementation • EACL 2021 • Beatrice Portelli, Edoardo Lenzi, Emmanuele Chersoni, Giuseppe Serra, Enrico Santus
Pretrained transformer-based models, such as BERT and its variants, have become a common choice to obtain state-of-the-art performances in NLP tasks.
1 code implementation • 13 Aug 2020 • Kevin Roitero, Michael Soprano, Beatrice Portelli, Damiano Spina, Vincenzo Della Mea, Giuseppe Serra, Stefano Mizzaro, Gianluca Demartini
Misinformation is an ever increasing problem that is difficult to solve for the research community and has a negative impact on the society at large.
no code implementations • WS 2020 • Beatrice Portelli, Jason Zhao, Tal Schuster, Giuseppe Serra, Enrico Santus
We propose, instead, a model-agnostic framework that consists of two modules: (1) a span extractor, which identifies the crucial information connecting claim and evidence; and (2) a classifier that combines claim, evidence, and the extracted spans to predict the veracity of the claim.