2 citations · 3 across the 4 of their papers we have counts for
5 papers · 1 filter
Enhancing Romanian Offensive Language Detection through Knowledge Distillation, Multi-Task Learning, and Data Augmentation
Vlad-Cristian Matei, Iulian-Marius Tăiatu, Răzvan-Alexandru Smădu +1
This paper highlights the significance of natural language processing (NLP) within artificial intelligence, underscoring its pivotal role in comprehending and modeling human langua…
From Fake to Hyperpartisan News Detection Using Domain Adaptation
Răzvan-Alexandru Smădu, Sebastian-Vasile Echim, Dumitru-Clementin Cercel +2
Unsupervised Domain Adaptation (UDA) is a popular technique that aims to reduce the domain shift between two data distributions. It was successfully applied in computer vision and…
TA-DA: Topic-Aware Domain Adaptation for Scientific Keyphrase Identification and Classification (Student Abstract)
Răzvan-Alexandru Smădu, George-Eduard Zaharia, Andrei-Marius Avram +3
Keyphrase identification and classification is a Natural Language Processing and Information Retrieval task that involves extracting relevant groups of words from a given text rela…
Domain Adaptation in Multilingual and Multi-Domain Monolingual Settings for Complex Word Identification
George-Eduard Zaharia, Răzvan-Alexandru Smădu, Dumitru-Clementin Cercel +1
Complex word identification (CWI) is a cornerstone process towards proper text simplification. CWI is highly dependent on context, whereas its difficulty is augmented by the scarci…
UPB at SemEval-2021 Task 7: Adversarial Multi-Task Learning for Detecting and Rating Humor and Offense
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. Neural netw…