Integrating LLMs in Gamified Systems
Not on the map. Why?
Abstract (arXiv)
In this work, a thorough mathematical framework for incorporating Large Language Models (LLMs) into gamified systems is presented with an emphasis on improving task dynamics, user engagement, and reward systems. Personalized feedback, adaptive learning, and dynamic content creation are all made possible by integrating LLMs and are crucial for improving user engagement and system performance. A simulated environment tests the framework's adaptability and demonstrates its potential for real-world applications in various industries, including business, healthcare, and education. The findings demonstrate how LLMs can offer customized experiences that raise system effectiveness and user retention. This study also examines the difficulties this framework aims to solve, highlighting its importance in maximizing involvement and encouraging sustained behavioral change in a range of sectors.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 5 of its 30 references that are in the map. First posted on arXiv 14 Mar 2025.
Builds on
5 of 30 references.
References · 5
- 2020Language Models are Few-Shot Learnerscited by 32,419
- 2024Personalization of Large Language Models: A Surveycited by 104
- 2023When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunitiescited by 90
- 2023Serious Games in Digital Gaming: A Comprehensive Review of Applications, Game Engines and Advancementscited by 2
- 2024Gamification and AI: Enhancing User Engagement through Intelligent Systemscited by 1
Built on by
Citing papers per year: 2025: 1.
1 paper.