85 citations · 143 across the 12 of their papers we have counts for
14 papers
Active Learning for Robust and Representative LLM Generation in Safety-Critical Scenarios
Sabit Hassan, Anthony Sicilia, Malihe Alikhani
Ensuring robust safety measures across a wide range of scenarios is crucial for user-facing systems. While Large Language Models (LLMs) can generate valuable data for safety measur…
Coherence-Driven Multimodal Safety Dialogue with Active Learning for Embodied Agents
Sabit Hassan, Hye-Young Chung, Xiang Zhi Tan +1
When assisting people in daily tasks, robots need to accurately interpret visual cues and respond effectively in diverse safety-critical situations, such as sharp objects on the fl…
An Active Learning Framework for Inclusive Generation by Large Language Models
Sabit Hassan, Anthony Sicilia, Malihe Alikhani
Ensuring that Large Language Models (LLMs) generate text representative of diverse sub-populations is essential, particularly when key concepts related to under-represented groups…
MedNgage: A Dataset for Understanding Engagement in Patient-Nurse Conversations
Yan Wang, Heidi Ann Scharf Donovan, Sabit Hassan +1
Patients who effectively manage their symptoms often demonstrate higher levels of engagement in conversations and interventions with healthcare practitioners. This engagement is mu…
D-CALM: A Dynamic Clustering-based Active Learning Approach for Mitigating Bias
Sabit Hassan, Malihe Alikhani
Despite recent advancements, NLP models continue to be vulnerable to bias. This bias often originates from the uneven distribution of real-world data and can propagate through the…
Multilingual Content Moderation: A Case Study on Reddit
Meng Ye, Karan Sikka, Katherine Atwell +3
Content moderation is the process of flagging content based on pre-defined platform rules. There has been a growing need for AI moderators to safeguard users as well as protect the…
APPDIA: A Discourse-aware Transformer-based Style Transfer Model for Offensive Social Media Conversations
Katherine Atwell, Sabit Hassan, Malihe Alikhani
Using style-transfer models to reduce offensiveness of social media comments can help foster a more inclusive environment. However, there are no sizable datasets that contain offen…
Modeling Intensification for Sign Language Generation: A Computational Approach
Mert İnan, Yang Zhong, Sabit Hassan +2
End-to-end sign language generation models do not accurately represent the prosody in sign language. A lack of temporal and spatial variations leads to poor-quality generated prese…
ArCovidVac: Analyzing Arabic Tweets About COVID-19 Vaccination
Hamdy Mubarak, Sabit Hassan, Shammur Absar Chowdhury +1
The emergence of the COVID-19 pandemic and the first global infodemic have changed our lives in many different ways. We relied on social media to get the latest information about t…
Emojis as Anchors to Detect Arabic Offensive Language and Hate Speech
Hamdy Mubarak, Sabit Hassan, Shammur Absar Chowdhury
We introduce a generic, language-independent method to collect a large percentage of offensive and hate tweets regardless of their topics or genres. We harness the extralinguistic…
Cross-lingual Emotion Detection
Sabit Hassan, Shaden Shaar, Kareem Darwish
Emotion detection can provide us with a window into understanding human behavior. Due to the complex dynamics of human emotions, however, constructing annotated datasets to train a…
Pre-Training BERT on Arabic Tweets: Practical Considerations
Ahmed Abdelali, Sabit Hassan, Hamdy Mubarak +2
Pretraining Bidirectional Encoder Representations from Transformers (BERT) for downstream NLP tasks is a non-trival task. We pretrained 5 BERT models that differ in the size of the…
ArCorona: Analyzing Arabic Tweets in the Early Days of Coronavirus (COVID-19) Pandemic
Hamdy Mubarak, Sabit Hassan
Over the past few months, there were huge numbers of circulating tweets and discussions about Coronavirus (COVID-19) in the Arab region. It is important for policy makers and many…
Arabic Dialect Identification in the Wild
Ahmed Abdelali, Hamdy Mubarak, Younes Samih +2
We present QADI, an automatically collected dataset of tweets belonging to a wide range of country-level Arabic dialects -covering 18 different countries in the Middle East and Nor…