Pre-trained language models (pLMs) learn intricate patterns and contextu...
Neuron analysis provides insights into how knowledge is structured in
re...
Work done to uncover the knowledge encoded within pre-trained language
m...
The proliferation of deep neural networks in various domains has seen an...
Neuron Interpretation has gained traction in the field of interpretabili...
The opacity of deep neural networks remains a challenge in deploying
sol...
We study the evolution of latent space in fine-tuned NLP models. Differe...
Arabic is a Semitic language which is widely spoken with many dialects. ...
We propose a novel framework ConceptX, to analyze how latent concepts ar...
While a lot of work has been done in understanding representations learn...
NatiQ is end-to-end text-to-speech system for Arabic. Our speech synthes...
A large number of studies that analyze deep neural network models and th...
Arabic is a Semitic language which is widely spoken with many dialects. ...
The proliferation of deep neural networks in various domains has seen an...
End-to-end DNN architectures have pushed the state-of-the-art in speech
...
Transfer learning from pre-trained neural language models towards downst...
This paper is a write-up for the tutorial on "Fine-grained Interpretatio...
Post-processing of static embedding has beenshown to improve their
perfo...
While a lot of analysis has been carried to demonstrate linguistic knowl...
With the outbreak of the COVID-19 pandemic, people turned to social medi...
This paper investigates contextual word representation models from the l...
Disinformation, i.e., information that is both false and means harm, thr...
Large pre-trained contextual word representations have transformed the f...
The ongoing neural revolution in Natural Language Processing has recentl...
Despite the recent success of deep neural networks in natural language
p...
We share the findings of the first shared task on improving robustness o...
We present a toolkit to facilitate the interpretation and understanding ...
Despite the remarkable evolution of deep neural networks in natural lang...
Neural machine translation (NMT) models learn representations containing...
We address the problem of simultaneous translation by modifying the Neur...
Bilingual sequence models improve phrase-based translation and reorderin...
While neural machine translation (NMT) models provide improved translati...
Word segmentation plays a pivotal role in improving any Arabic NLP
appli...
In this paper, we explore alternative ways to train a neural machine
tra...
Neural machine translation (MT) models obtain state-of-the-art performan...
In this study, we present an analysis regarding the performance of the
s...
This paper describes QCRI's machine translation systems for the IWSLT 20...
We present research towards bridging the language gap between migrant wo...
The paper describes the Egyptian Arabic-to-English statistical machine
t...