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This paper introduces a novel integration of Retrieval-Augmented Generation (RAG) enhanced Large Language Models (LLMs) with Extended Reality (XR) technologies to address knowledge transfer challenges in industrial environments.
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A. Gezdur and J. Bhattacharjya, “Innovators and transformers: enhancing supply chain employee training with an innovative application of a large language model,” International Journal of Physical Distribution & Logistics Management , 2025, publisher: Emerald Publishing Limited. [Online]. Available: https://www.emerald.com/insight/content/doi/10.1108/ijpdlm-12-2023-0492/full/html
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A. Kiourtis, A. Mavrogiorgou, G. Makridis, D. Kyriazis, J. Soldatos, G. Fatouros, D. Ntalaperas, X. Papageorgiou, B. Almeida, J. Guedes et al. , “Xr5. 0: Human-centric ai-enabled extended reality applications for industry 5.0,” in 2024 36th Conference of Open Innovations Association (FRUCT) . IEEE, 2024, pp. 314–323
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M. Shao, A. Basit, R. Karri, and M. Shafique, “Survey of Different Large Language Model Architectures: Trends, Benchmarks, and Challenges,” IEEE Access , vol. 12, pp. 188 664–188 706, 2024, publisher: Institute of Electrical and Electronics Engineers (IEEE). [Online]. Available: http://dx.doi.org/10.1109/ACCESS.2024.3482107
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M. Baptista, N. Yue, M. M. M. Islam, and H. Prendinger, Large Language Models (LLMs) for Smart Manufacturing and Industry X.0 , 03 2025, pp. 97–119
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