5 papers
Adversarial Diffusion Across Modalities: A Fusion Survey of Attacks, Defenses, and Evaluation for Text, Vision, and Vision-Language Models
Abrar Alotaibi, Moataz Ahmed
Adversarial evaluation of AI systems has matured along four largely disconnected tracks: diffusion-based attacks on text and large language models (LLMs), diffusion-based attacks o…
A Red Teaming Framework for Large Language Models: A Case Study on Faithfulness Evaluation
Abrar Alotaibi, Raed Mughus, Moataz Ahmed
Large language models (LLMs) have demonstrated remarkable performance across natural language processing tasks, yet their deployment in high-stakes applications raises critical con…
Are We Aligned? A Preliminary Investigation of the Alignment of Responsible AI Values between LLMs and Human Judgment
Asma Yamani, Malak Baslyman, Moataz Ahmed
Large Language Models (LLMs) are increasingly employed in software engineering tasks such as requirements elicitation, design, and evaluation, raising critical questions regarding…
Peering Inside the Black Box: Uncovering LLM Errors in Optimization Modelling through Component-Level Evaluation
Dania Refai, Moataz Ahmed
Large language models (LLMs) are increasingly used to convert natural language descriptions into mathematical optimization formulations. Current evaluations often treat formulation…
Multi-Agent LLMs as Ethics Advocates for AI-Based Systems
Asma Yamani, Malak Baslyman, Moataz Ahmed
Incorporating ethics into the requirement elicitation process is essential for creating ethically aligned systems. Although eliciting manual ethics requirements is effective, it re…