A comprehensive overview of large language models

H Naveed, AU Khan, S Qiu, M Saqib, S Anwar… - arxiv preprint arxiv …, 2023 - arxiv.org
Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

Against The Achilles' Heel: A Survey on Red Teaming for Generative Models

L Lin, H Mu, Z Zhai, M Wang, Y Wang, R Wang… - Journal of Artificial …, 2025 - jair.org
Generative models are rapidly gaining popularity and being integrated into everyday
applications, raising concerns over their safe use as various vulnerabilities are exposed. In …

Goal-guided generative prompt injection attack on large language models

C Zhang, M **, Q Yu, C Liu, H Xue, X ** - arxiv preprint arxiv …, 2024 - arxiv.org
Current large language models (LLMs) provide a strong foundation for large-scale user-
oriented natural language tasks. A large number of users can easily inject adversarial text or …

[PDF][PDF] Os agents: A survey on mllm-based agents for general computing devices use

X Hu, T **ong, B Yi, Z Wei, R **ao, Y Chen, J Ye, M Tao… - 2024 - preprints.org
The dream to create AI assistants as capable and versatile as the fictional JARVIS from Iron
Man has long captivated imaginations. With the evolution of (multimodal) large language …

Bias Beware: The Impact of Cognitive Biases on LLM-Driven Product Recommendations

G Filandrianos, A Dimitriou, M Lymperaiou… - arxiv preprint arxiv …, 2025 - arxiv.org
The advent of Large Language Models (LLMs) has revolutionized product recommendation
systems, yet their susceptibility to adversarial manipulation poses critical challenges …