most citedMulti-Agent LLMs as Ethics Advocates for AI-Based Systems

3 citations · 3 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Structured Stateful Relational Scripts with a High-Quality Dataset for Multi-Shot Audio-Visual Video Generation

Chen Zhao, Lehan Shen, Qilong Huang +5

Coherent multi-shot audio-visual video generation requires maintaining consistent identities while depicting evolving states and coordinating sounds across shot boundaries. Althoug…

cs.CR2026

Layered LLM Defenses as an Ensemble: Access Tiers, Inference Cost, and the Measured Failure Correlation Between Defense Layers

Abrar Alotaibi, Muhammad Shahid Jabbar, Sadam Al-Azani +1

Practitioners defend large language models (LLMs) by stacking defenses, assuming the layers compound. A stack is an ensemble, and ensembles compound only under a condition the LLM…

cs.CL2026

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…

cs.CR2026

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…

cs.SE2025

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…

cs.LG2025

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…

cs.AI2025★ 3 cited

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…