3 citations · 4 across the 5 of their papers we have counts for
5 papers
Budget-Constrained Online Retrieval-Augmented Generation: The Chunk-as-a-Service Model
Shawqi Al-Maliki, Ammar Gharaibeh, Mohamed Rahouti +4
Large Language Models (LLMs) have revolutionized the field of natural language processing. However, they exhibit some limitations, including a lack of reliability and transparency:…
A Multi-Perspective Benchmark and Moderation Model for Evaluating Safety and Adversarial Robustness
Naseem Machlovi, Maryam Saleki, Ruhul Amin +5
As large language models (LLMs) become deeply embedded in daily life, the urgent need for safer moderation systems that distinguish between naive and harmful requests while upholdi…
Can LLMs Write Faithfully? An Agent-Based Evaluation of LLM-generated Islamic Content
Abdullah Mushtaq, Rafay Naeem, Ezieddin Elmahjub +5
Large language models are increasingly used for Islamic guidance, but risk misquoting texts, misapplying jurisprudence, or producing culturally inconsistent responses. We pilot an…
Adversarial Machine Learning for Social Good: Reframing the Adversary as an Ally
Shawqi Al-Maliki, Adnan Qayyum, Hassan Ali +5
Deep Neural Networks (DNNs) have been the driving force behind many of the recent advances in machine learning. However, research has shown that DNNs are vulnerable to adversarial…
Addressing Data Distribution Shifts in Online Machine Learning Powered Smart City Applications Using Augmented Test-Time Adaptation
Shawqi Al-Maliki, Faissal El Bouanani, Mohamed Abdallah +2
Data distribution shift is a common problem in machine learning-powered smart city applications where the test data differs from the training data. Augmenting smart city applicatio…