57 citations · 190 across the 32 of their papers we have counts for
27 papers · 1 filter
LatentMT: Machine Translation with Latent Reasoning
Wei-Rui Chen, Samar M. Magdy, Chiyu Zhang +3
Latent-reasoning looped language models (LoopLMs) offer a different scaling path for machine translation (MT): instead of increasing parameter count or emitting explicit chain-of-t…
NADI 2025: The First Multidialectal Arabic Speech Processing Shared Task
Bashar Talafha, Hawau Olamide Toyin, Peter Sullivan +9
We present the findings of the sixth Nuanced Arabic Dialect Identification (NADI 2025) Shared Task, which focused on Arabic speech dialect processing across three subtasks: spoken…
DefenderBench: A Toolkit for Evaluating Language Agents in Cybersecurity Environments
Chiyu Zhang, Marc-Alexandre Cote, Michael Albada +6
Large language model (LLM) agents have shown impressive capabilities in human language comprehension and reasoning, yet their potential in cybersecurity remains underexplored. We i…
NADI 2024: The Fifth Nuanced Arabic Dialect Identification Shared Task
Muhammad Abdul-Mageed, Amr Keleg, AbdelRahim Elmadany +5
We describe the findings of the fifth Nuanced Arabic Dialect Identification Shared Task (NADI 2024). NADI's objective is to help advance SoTA Arabic NLP by providing guidance, data…
Distilling Text Style Transfer With Self-Explanation From LLMs
Chiyu Zhang, Honglong Cai, Yuezhang +4
Text Style Transfer (TST) seeks to alter the style of text while retaining its core content. Given the constraints of limited parallel datasets for TST, we propose CoTeX, a framewo…
LLM-Assisted Content Conditional Debiasing for Fair Text Embedding
Wenlong Deng, Blair Chen, Beidi Zhao +3
Mitigating biases in machine learning models has become an increasing concern in Natural Language Processing (NLP), particularly in developing fair text embeddings, which are cruci…
Demystifying Instruction Mixing for Fine-tuning Large Language Models
Renxi Wang, Haonan Li, Minghao Wu +4
Instruction tuning significantly enhances the performance of large language models (LLMs) across various tasks. However, the procedure to optimizing the mixing of instruction datas…
NADI 2023: The Fourth Nuanced Arabic Dialect Identification Shared Task
Muhammad Abdul-Mageed, AbdelRahim Elmadany, Chiyu Zhang +3
We describe the findings of the fourth Nuanced Arabic Dialect Identification Shared Task (NADI 2023). The objective of NADI is to help advance state-of-the-art Arabic NLP by creati…
The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languages
Chiyu Zhang, Khai Duy Doan, Qisheng Liao +1
Instruction tuned large language models (LLMs), such as ChatGPT, demonstrate remarkable performance in a wide range of tasks. Despite numerous recent studies that examine the perfo…
LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions
Minghao Wu, Abdul Waheed, Chiyu Zhang +2
Large language models (LLMs) with instruction fine-tuning demonstrate superior generative capabilities. However, these models are resource-intensive. To alleviate this issue, we ex…
NADI 2022: The Third Nuanced Arabic Dialect Identification Shared Task
Muhammad Abdul-Mageed, Chiyu Zhang, AbdelRahim Elmadany +2
We describe findings of the third Nuanced Arabic Dialect Identification Shared Task (NADI 2022). NADI aims at advancing state of the art Arabic NLP, including on Arabic dialects. I…
Transition to Adulthood for Young People with Intellectual or Developmental Disabilities: Emotion Detection and Topic Modeling
Yan Liu, Maria Laricheva, Chiyu Zhang +5
Transition to Adulthood is an essential life stage for many families. The prior research has shown that young people with intellectual or development disabil-ities (IDD) have more…
Automated Utterance Labeling of Conversations Using Natural Language Processing
Maria Laricheva, Chiyu Zhang, Yan Liu +4
Conversational data is essential in psychology because it can help researchers understand individuals cognitive processes, emotions, and behaviors. Utterance labelling is a common…
Decay No More: A Persistent Twitter Dataset for Learning Social Meaning
Chiyu Zhang, Muhammad Abdul-Mageed, El Moatez Billah Nagoudi
With the proliferation of social media, many studies resort to social media to construct datasets for developing social meaning understanding systems. For the popular case of Twitt…
Contrastive Learning of Sociopragmatic Meaning in Social Media
Chiyu Zhang, Muhammad Abdul-Mageed, Ganesh Jawahar
Recent progress in representation and contrastive learning in NLP has not widely considered the class of \textit{sociopragmatic meaning} (i.e., meaning in interaction within differ…
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…
NADI 2021: The Second Nuanced Arabic Dialect Identification Shared Task
Muhammad Abdul-Mageed, Chiyu Zhang, AbdelRahim Elmadany +2
We present the findings and results of the Second Nuanced Arabic Dialect Identification Shared Task (NADI 2021). This Shared Task includes four subtasks: country-level Modern Stand…
NADI 2020: The First Nuanced Arabic Dialect Identification Shared Task
Muhammad Abdul-Mageed, Chiyu Zhang, Houda Bouamor +1
We present the results and findings of the First Nuanced Arabic Dialect Identification Shared Task (NADI). This Shared Task includes two subtasks: country-level dialect identificat…
Toward Micro-Dialect Identification in Diaglossic and Code-Switched Environments
Muhammad Abdul-Mageed, Chiyu Zhang, AbdelRahim Elmadany +1
Although the prediction of dialects is an important language processing task, with a wide range of applications, existing work is largely limited to coarse-grained varieties. Inspi…
Leveraging Affective Bidirectional Transformers for Offensive Language Detection
AbdelRahim Elmadany, Chiyu Zhang, Muhammad Abdul-Mageed +1
Social media are pervasive in our life, making it necessary to ensure safe online experiences by detecting and removing offensive and hate speech. In this work, we report our submi…
AraNet: A Deep Learning Toolkit for Arabic Social Media
Muhammad Abdul-Mageed, Chiyu Zhang, Azadeh Hashemi +1
We describe AraNet, a collection of deep learning Arabic social media processing tools. Namely, we exploit an extensive host of publicly available and novel social media datasets t…
Sentence-Level BERT and Multi-Task Learning of Age and Gender in Social Media
Muhammad Abdul-Mageed, Chiyu Zhang, Arun Rajendran +3
Social media currently provide a window on our lives, making it possible to learn how people from different places, with different backgrounds, ages, and genders use language. In t…
DiaNet: BERT and Hierarchical Attention Multi-Task Learning of Fine-Grained Dialect
Muhammad Abdul-Mageed, Chiyu Zhang, AbdelRahim Elmadany +2
Prediction of language varieties and dialects is an important language processing task, with a wide range of applications. For Arabic, the native tongue of ~ 300 million people, mo…
BERT-Based Arabic Social Media Author Profiling
Chiyu Zhang, Muhammad Abdul-Mageed
We report our models for detecting age, language variety, and gender from social media data in the context of the Arabic author profiling and deception detection shared task (APDA)…