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Results for "prompt engineering"

LLM-based Multi-class Attack Analysis and Mitigation Framework in IoT/IIoT Networks

arXiv · Oct 30

This paper introduces a framework that combines machine learning for multi-class attack detection in IoT/IIoT networks with large language models (LLMs) for attack behavior analysis and mitigation suggestion. The framework uses role-play prompt engineering with RAG to guide LLMs like ChatGPT-o3 and DeepSeek-R1, and introduces new evaluation metrics for quantitative assessment. Experiments using Edge-IIoTset and CICIoT2023 datasets showed Random Forest as the best detection model and ChatGPT-o3 outperforming DeepSeek-R1 in attack analysis and mitigation.

Large Language Models and Arabic Content: A Review

arXiv · May 12

This study reviews the use of large language models (LLMs) for Arabic language processing, focusing on pre-trained models and their applications. It highlights the challenges in Arabic NLP due to the language's complexity and the relative scarcity of resources. The review also discusses how techniques like fine-tuning and prompt engineering enhance model performance on Arabic benchmarks. Why it matters: This overview helps consolidate research directions and benchmarks in Arabic NLP, guiding future development of LLMs tailored for the Arabic language and its diverse dialects.

MBZUAI Launches “WAI” Community Initiative to build AI Awareness across Generations

MBZUAI · Invalid Date

MBZUAI has launched "WAI", a community initiative to provide youth and senior citizens with a foundational understanding of AI and its applications. The inaugural event hosted over 30 youth and 15 senior citizens at MBZUAI’s campus for a day of learning and discussion. The program includes interactive sessions and hands-on activities in prompt engineering, with all participants receiving certificates of completion. Why it matters: This initiative promotes AI awareness across generations and aligns with the UAE’s Year of Community 2025, fostering inclusivity and shared learning in the digital age.