Future Applications of Large Language Models

Dear Colleagues,

Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse tasks, from text generation and translation to code synthesis and question-answering. However, their true potential lies beyond current applications and into the realm of complex, interactive AI systems. This Special Issue will explore the exciting future directions of LLM research, focusing on how these powerful models can be leveraged to create truly intelligent and helpful tools.

We are seeking contributions concerning any envisaged LLM application domain. A promising example is Explainable AI (XAI). While XAI is relatively mature in areas like text classification, its application to text generation remains nascent. Current approaches often rely on identifying and linking relevant text spans from the training corpus as "citations" for generated output. Another compelling direction is the agentic approach, which involves orchestrating multiple LLM instances (or prompts) to perform complex tasks. This has the potential to significantly broaden LLM applicability across general and specialized domains. Also, multimodal LLMs represent a key development area, capable of synergistic analysis of diverse data sources that are typically handled separately.

This Special Issue aims to bring together researchers from diverse fields, including Natural Language Processing, Artificial Intelligence, cognitive science, and human–computer interactions, to explore the transformative potential of LLMs. We encourage submissions presenting novel research, insightful perspectives, and innovative applications in these crucial areas, particularly those addressing explainability, agentic behavior, and multimodality.

Dr. Luigi Laura
Prof. Dr. Maurizio Naldi
Guest Editors

Dr. Paolo Fantozzi
Guest Editor Assistant

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