The exponential rise in the use of Large Language Models (LLMs) and Generative Artificial Intelligence (GAI) has revolutionized human-computer interaction. Unlike traditional computational systems, LLMs have introduced new dimensions in how humans engage with technology, raising pivotal questions about the nature of these interactions. Concurrently, the application of LLMs within the Cognitive Sciences has propelled significant advances in understanding human cognition, particularly in distinguishing it from LLM-generated processes. Efforts to connect these dual areas of research remain scarce, highlighting a missed opportunity to enrich both fields.

This Research Topic aims to bridge the gap between LLM-human interaction studies and cognitive science by integrating insights from the two domains. Specifically, it focuses on the potential of LLMs to inform cognitive modeling and enhance our understanding of human cognition through parallels and contrasts with LLM behavior. Questions about behavior cloning, recommendation systems, and personalization arise as critical areas for exploration. Additionally, the research seeks to identify methodologies to refine LLMs inclusively, addressing aspects such as diversity, equity, and inclusion.

To gather further insights into the intersection of cognitive science and LLM applications, we welcome articles addressing, but not limited to, the following themes:

- Comparative analyses of human and LLM behavior
- Applications of LLMs in cognitive modeling
- Studies on human-LLM interaction
- Methods to enhance diversity, equity, and inclusion in LLM usage
- Innovative approaches to impacting human-AI teaming and personalization

This Research Topic invites submissions that transcend these examples while remaining within the broader scope of human cognition and large language model research. Various article types, including original research and systematic reviews, are encouraged in collaboration with Frontiers in Computer Science and Frontiers in Psychology.

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Exploring the Intersection of Human Cognition and Large Language Model Interaction