Search Results for author: George-Eduard Zaharia

Found 9 papers, 0 papers with code

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-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

Exploring the Power of Romanian BERT for Dialect Identification

no code implementations VarDial (COLING) 2020 George-Eduard Zaharia, Andrei-Marius Avram, Dumitru-Clementin Cercel, Traian Rebedea

Dialect identification represents a key aspect for improving a series of tasks, for example, opinion mining, considering that the location of the speaker can greatly influence the attitude towards a subject.

Dialect Identification Opinion Mining

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

TA-DA: Topic-Aware Domain Adaptation for Scientific Keyphrase Identification and Classification (Student Abstract)

no code implementations30 Dec 2022 Răzvan-Alexandru Smădu, George-Eduard Zaharia, Andrei-Marius Avram, Dumitru-Clementin Cercel, Mihai Dascalu, Florin Pop

Keyphrase identification and classification is a Natural Language Processing and Information Retrieval task that involves extracting relevant groups of words from a given text related to the main topic.

Domain Adaptation Information Retrieval +3

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