Recently, large language models (LLMs) fine-tuned to follow human instru...
Large language models (LLMs) finetuned to follow human instructions have...
Weight-sharing supernet has become a vital component for performance
est...
Whisper, the recently developed multilingual weakly supervised model, is...
Arabic dialect identification (ADI) tools are an important part of the
l...
We present Dolphin, a novel benchmark that addresses the need for an
eva...
The recent emergence of ChatGPT has brought a revolutionary change in th...
Large language models (LLMs) with instruction finetuning demonstrate sup...
Intent detection and slot filling are critical tasks in spoken and natur...
We describe our contribution to the SemEVAl 2023 AfriSenti-SemEval share...
Multilingual language models (MLMs) acquire valuable, generalizable
ling...
Due to their crucial role in all NLP, several benchmarks have been propo...
Task agnostic generative pretraining (GPT) has recently proved promising...
The prevalence of abusive language on different online platforms has bee...
Contrastive learning (CL) brought significant progress to various NLP ta...
Language identification (LID) is a crucial precursor for NLP, especially...
We describe findings of the third Nuanced Arabic Dialect Identification
...
Neural architecture search (NAS) has demonstrated promising results on
i...
We present TURJUMAN, a neural toolkit for translating from 20 languages ...
Machine translation (MT) involving Indigenous languages, including those...
With the proliferation of social media, many studies resort to social me...
In this work, we focus on the problem of distinguishing a human written ...
Aligning with ACL 2022 special Theme on "Language Diversity: from Low
Re...
Existing supervised contrastive learning frameworks suffer from two majo...
ASR systems designed for native English (L1) usually underperform on
non...
To address the performance gap of English ASR models on L2 English speak...
Transfer learning has been an important technique for low-resource neura...
We investigate transfer learning based on pre-trained neural machine
tra...
Masked language models (MLMs) are pretrained with a denoising objective ...
Recent progress in neural machine translation (NMT) has made it possible...
We describe models focused at the understudied problem of translating be...
With the continuing spread of misinformation and disinformation online, ...
Translating between languages where certain features are marked
morpholo...
We present the findings and results of the Second Nuanced Arabic Dialect...
A sufficient amount of annotated data is usually required to fine-tune
p...
Masked language models (MLM) have become an integral part of many natura...
Word embeddings are a core component of modern natural language processi...
We investigate different approaches to translate between similar languag...
Fake news and deceptive machine-generated text are serious problems
thre...
Text generative models (TGMs) excel in producing text that matches the s...
We present the results and findings of the First Nuanced Arabic Dialect
...
Although the prediction of dialects is an important language processing ...
The task of grapheme-to-phoneme (G2P) conversion is important for both s...
We describe our submission to the 2020 Duolingo Shared Task on Simultane...
Social media communication has become a significant part of daily activi...
We describe Mega-COV, a billion-scale dataset from Twitter for studying
...
We describe AraNet, a collection of deep learning Arabic social media
pr...
Social media currently provide a window on our lives, making it possible...
Prediction of language varieties and dialects is an important language
p...
We report our models for detecting age, language variety, and gender fro...