57 citations · 257 across the 33 of their papers we have counts for
11 papers · 1 filter
Machine Translation of Low-Resource Indo-European Languages
Wei-Rui Chen, Muhammad Abdul-Mageed
In this work, we investigate methods for the challenging task of translating between low-resource language pairs that exhibit some level of similarity. In particular, we consider t…
AraT5: Text-to-Text Transformers for Arabic Language Generation
El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed
Transfer learning with a unified Transformer framework (T5) that converts all language problems into a text-to-text format was recently proposed as a simple and effective transfer…
Improving Similar Language Translation With Transfer Learning
Ife Adebara, Muhammad Abdul-Mageed
We investigate transfer learning based on pre-trained neural machine translation models to translate between (low-resource) similar languages. This work is part of our contribution…
Improving Social Meaning Detection with Pragmatic Masking and Surrogate Fine-Tuning
Chiyu Zhang, Muhammad Abdul-Mageed
Masked language models (MLMs) are pre-trained with a denoising objective that is in a mismatch with the objective of downstream fine-tuning. We propose pragmatic masking and surrog…
Investigating Code-Mixed Modern Standard Arabic-Egyptian to English Machine Translation
El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed
Recent progress in neural machine translation (NMT) has made it possible to translate successfully between monolingual language pairs where large parallel data exist, with pre-trai…
Exploring Text-to-Text Transformers for English to Hinglish Machine Translation with Synthetic Code-Mixing
Ganesh Jawahar, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed +1
We describe models focused at the understudied problem of translating between monolingual and code-mixed language pairs. More specifically, we offer a wide range of models that con…