Generative AI, Large Language Models and Their Applications

Dear Colleagues,

Recent breakthroughs in foundation models and generative AI, including multimodal LLMs and autonomous agents, are reshaping artificial intelligence research and practical applications. This Special Issue, titled "Generative AI, Large Language Models and Their Applications," aims to provide an interdisciplinary overview of advancements in generative AI, especially focusing on large language models (LLMs).

This Special Issue covers methodological innovations, novel model architectures, training paradigms, evaluation methodologies, and real-world applications in sectors like education, healthcare, business, and creative industries. It seeks to highlight both the performance and limitations of LLMs, as well as the broader societal implications, including explainable AI, ethics, and responsible AI.

By integrating insights from various disciplines, this Special Issue will serve as a resource for researchers and practitioners, emphasizing the importance of bridging symbolic and neural approaches in the development of hybrid, knowledge-driven AI systems.

Topics include (but are not limited to) the following:

• Large language models and foundation models;
• Multimodal generative AI;
• Prompting, fine-tuning, and alignment methods;
• Neuro-symbolic and hybrid AI systems;
• Knowledge graphs and LLM integration;
• Explainability and interpretability of generative models;
• Evaluation and benchmarking of LLMs;
• Bias, fairness, and responsible AI;
• Domain-specific applications (e.g., healthcare, education, industry);
• Human–AI collaboration and interaction.

Dr. Agnieszka Konys
Guest Editor

Manuscript Submission Information

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