6 papers
A multitask learning framework for leveraging subjectivity of annotators to identify misogyny
Jason Angel, Segun Taofeek Aroyehun, Grigori Sidorov +1
Identifying misogyny using artificial intelligence is a form of combating online toxicity against women. However, the subjective nature of interpreting misogyny poses a significant…
Utilizing deep learning models for the identification of enhancers and super-enhancers based on genomic and epigenomic features
Zahra Ahani, Moein Shahiki Tash, Yoel Ledo Mezquita +1
This paper provides an extensive examination of a sizable dataset of English tweets focusing on nine widely recognized cryptocurrencies, specifically Cardano, Binance, Bitcoin, Dog…
Leveraging the power of transformers for guilt detection in text
Abdul Gafar Manuel Meque, Jason Angel, Grigori Sidorov +1
In recent years, language models and deep learning techniques have revolutionized natural language processing tasks, including emotion detection. However, the specific emotion of g…
NLP-CIC @ PRELEARN: Mastering prerequisites relations, from handcrafted features to embeddings
Jason Angel, Segun Taofeek Aroyehun, Alexander Gelbukh
We present our systems and findings for the prerequisite relation learning task (PRELEARN) at EVALITA 2020. The task aims to classify whether a pair of concepts hold a prerequisite…
NLP-CIC @ DIACR-Ita: POS and Neighbor Based Distributional Models for Lexical Semantic Change in Diachronic Italian Corpora
Jason Angel, Carlos A. Rodriguez-Diaz, Alexander Gelbukh +1
We present our systems and findings on unsupervised lexical semantic change for the Italian language in the DIACR-Ita shared-task at EVALITA 2020. The task is to determine whether…
NLP-CIC at SemEval-2020 Task 9: Analysing sentiment in code-switching language using a simple deep-learning classifier
Jason Angel, Segun Taofeek Aroyehun, Antonio Tamayo +1
Code-switching is a phenomenon in which two or more languages are used in the same message. Nowadays, it is quite common to find messages with languages mixed in social media. This…