8 citations · 12 across the 8 of their papers we have counts for
8 papers · 1 filter
Syntactic Knowledge via Graph Attention with BERT in Machine Translation
Yuqian Dai, Serge Sharoff, Marc de Kamps
Although the Transformer model can effectively acquire context features via a self-attention mechanism, deeper syntactic knowledge is still not effectively modeled. To alleviate th…
GATology for Linguistics: What Syntactic Dependencies It Knows
Yuqian Dai, Serge Sharoff, Marc de Kamps
Graph Attention Network (GAT) is a graph neural network which is one of the strategies for modeling and representing explicit syntactic knowledge and can work with pre-trained mode…
Estimating Confidence of Predictions of Individual Classifiers and Their Ensembles for the Genre Classification Task
Mikhail Lepekhin, Serge Sharoff
Genre identification is a subclass of non-topical text classification. The main difference between this task and topical classification is that genres, unlike topics, usually do no…
Towards Arabic Sentence Simplification via Classification and Generative Approaches
Nouran Khallaf, Serge Sharoff
This paper presents an attempt to build a Modern Standard Arabic (MSA) sentence-level simplification system. We experimented with sentence simplification using two approaches: (i)…
Experiments with adversarial attacks on text genres
Mikhail Lepekhin, Serge Sharoff
Neural models based on pre-trained transformers, such as BERT or XLM-RoBERTa, demonstrate SOTA results in many NLP tasks, including non-topical classification, such as genre identi…
Automatic Difficulty Classification of Arabic Sentences
Nouran Khallaf, Serge Sharoff
In this paper, we present a Modern Standard Arabic (MSA) Sentence difficulty classifier, which predicts the difficulty of sentences for language learners using either the CEFR prof…