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Found 15 papers, 5 papers with code
A Framework for Identifying Depression on Social Media: MentalRiskES@IberLEF 2023
This paper describes our participation in the MentalRiskES task at IberLEF 2023.
HULAT at SemEval-2023 Task 10: Data augmentation for pre-trained transformers applied to the detection of sexism in social media
This paper describes our participation in SemEval-2023 Task 10, whose goal is the detection of sexism in social media.
HULAT at SemEval-2023 Task 9: Data augmentation for pre-trained transformers applied to Multilingual Tweet Intimacy Analysis
During the development phase, our best results were obtained by using XLM-T. Data augmentation techniques provide a very slight improvement in the results.
Multimodal Fake News Detection
Some fake news categories such as Manipulated content, Satire or False connection strongly benefit from the use of images.
Exploring deep learning methods for recognizing rare diseases and their clinical manifestations from texts
The paper explores the use of several deep learning techniques such as Bidirectional Long Short Term Memory (BiLSTM) networks or deep contextualized word representations based on Bidirectional Encoder Representations from Transformers (BERT) to recognize rare diseases and their clinical manifestations (signs and symptoms) in the RareDis corpus.
The RareDis corpus: a corpus annotated with rare diseases, their signs and symptoms
The RareDis corpus contains more than 5, 000 rare diseases and almost 6, 000 clinical manifestations are annotated.
UC3M-NII Team at SemEval-2018 Task 7: Semantic Relation Classification in Scientific Papers via Convolutional Neural Network
This paper reports our participation for SemEval-2018 Task 7 on extraction and classification of relationships between entities in scientific papers.
LABDA at SemEval-2017 Task 10: Extracting Keyphrases from Scientific Publications by combining the BANNER tool and the UMLS Semantic Network
For the task of identification, we use the BANNER tool, a named entity recognition system, which is based on conditional random fields (CRF) and has obtained successful results in the biomedical domain.
LABDA at SemEval-2017 Task 10: Relation Classification between keyphrases via Convolutional Neural Network
In this paper, we describe our participation at the subtask of extraction of relationships between two identified keyphrases.
Exploring Convolutional Neural Networks for Sentiment Analysis of Spanish tweets
Spanish is the third-most used language on the internet, after English and Chinese, with a total of 7. 7{\%} (more than 277 million of users) and a huge internet growth of more than 1, 400{\%}.
