Search Results for author: Mihai Dascalu

Found 14 papers, 2 papers with code

Interpretable Identification of Cybersecurity Vulnerabilities from News Articles

no code implementations RANLP 2021 Pierre Frode de la Foret, Stefan Ruseti, Cristian Sandescu, Mihai Dascalu, Sebastien Travadel

Various automated processing pipelines grounded in Natural Language Processing techniques for text classification were introduced for the early identification of vulnerabilities starting from Open-Source Intelligence (OSINT) data, including news websites, blogs, and social media.

text-classification Text Classification

UPB at SemEval-2022 Task 5: Enhancing UNITER with Image Sentiment and Graph Convolutional Networks for Multimedia Automatic Misogyny Identification

1 code implementation SemEval (NAACL) 2022 Andrei Paraschiv, Mihai Dascalu, Dumitru-Clementin Cercel

In recent times, the detection of hate-speech, offensive, or abusive language in online media has become an important topic in NLP research due to the exponential growth of social media and the propagation of such messages, as well as their impact.

Abusive Language Hate Speech Detection

Domain Adaptation in Multilingual and Multi-Domain Monolingual Settings for Complex Word Identification

no code implementations ACL 2022 George-Eduard Zaharia, Răzvan-Alexandru Smădu, Dumitru-Clementin Cercel, Mihai Dascalu

Our model obtains a boost of up to 2. 42% in terms of Pearson Correlation Coefficients in contrast to vanilla training techniques, when considering the CompLex from the Lexical Complexity Prediction 2021 dataset.

Complex Word Identification Domain Adaptation +2

UPB at SemEval-2021 Task 5: Virtual Adversarial Training for Toxic Spans Detection

no code implementations SEMEVAL 2021 Andrei Paraschiv, Dumitru-Clementin Cercel, Mihai Dascalu

The real-world impact of polarization and toxicity in the online sphere marked the end of 2020 and the beginning of this year in a negative way.

Toxic Spans Detection

UPB at SemEval-2021 Task 1: Combining Deep Learning and Hand-Crafted Features for Lexical Complexity Prediction

no code implementations SEMEVAL 2021 George-Eduard Zaharia, Dumitru-Clementin Cercel, Mihai Dascalu

Our models are applicable on both subtasks and achieve good performance results, with a MAE below 0. 07 and a Person correlation of . 73 for single word identification, as well as a MAE below 0. 08 and a Person correlation of . 79 for multiple word targets.

Lexical Complexity Prediction Word Embeddings

UPB at SemEval-2021 Task 7: Adversarial Multi-Task Learning for Detecting and Rating Humor and Offense

no code implementations SEMEVAL 2021 Răzvan-Alexandru Smădu, Dumitru-Clementin Cercel, Mihai Dascalu

Detecting humor is a challenging task since words might share multiple valences and, depending on the context, the same words can be even used in offensive expressions.

Multi-Task Learning text-classification +1

RoBERT -- A Romanian BERT Model

no code implementations COLING 2020 Mihai Masala, Stefan Ruseti, Mihai Dascalu

Deep pre-trained language models tend to become ubiquitous in the field of Natural Language Processing (NLP).

Sentiment Analysis Transfer Learning

Cross-Lingual Transfer Learning for Complex Word Identification

no code implementations2 Oct 2020 George-Eduard Zaharia, Dumitru-Clementin Cercel, Mihai Dascalu

Our aim is to provide evidence that the proposed models can learn the characteristics of complex words in a multilingual environment by relying on the CWI shared task 2018 dataset available for four different languages (i. e., English, German, Spanish, and also French).

Complex Word Identification Cross-Lingual Transfer +3

UPB at SemEval-2020 Task 11: Propaganda Detection with Domain-Specific Trained BERT

no code implementations SEMEVAL 2020 Andrei Paraschiv, Dumitru-Clementin Cercel, Mihai Dascalu

Manipulative and misleading news have become a commodity for some online news outlets and these news have gained a significant impact on the global mindset of people.

Propaganda span identification

Romanian Diacritics Restoration Using Recurrent Neural Networks

no code implementations6 Sep 2020 Stefan Ruseti, Teodor-Mihai Cotet, Mihai Dascalu

Diacritics restoration is a mandatory step for adequately processing Romanian texts, and not a trivial one, as you generally need context in order to properly restore a character.

Building a Comprehensive Romanian Knowledge Base for Drug Administration

no code implementations RANLP 2019 Bogdan Nicula, Mihai Dascalu, Maria-Dorinela S{\^\i}rbu, {\textcommabelow{S}}tefan Tr{\u{a}}u{\textcommabelow{s}}an-Matu, Alex Nu{\textcommabelow{t}}{\u{a}}, ru

Information on drug administration is obtained traditionally from doctors and pharmacists, as well as leaflets which provide in most cases cumbersome and hard-to-follow details.

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