VectorizationLLM: Smart Vectorization Based AI Assistant
VectorizationLLM is a specialized large language model based on Google open-weight LLMs, designed to help students learn smart vectorization and related topics in MATLAB for the course CTEC 247 at New York Institute of Technology. It uses a RAG knowledge base and system prompts to provide explanations and examples without giving direct answers.
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[Submitted on 8 Jul 2026]
Title:VectorizationLLM: Smart Vectorization Based AI Assistant
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Abstract:VectorizationLLM is a specialized Large Language Model based on Google open-weight LLMs. The model is designed to assist students to learn smart vectorization, time/wave vector analysis, piecewise functions, Fourier analysis, and differential equations in MATLAB. The course application is CTEC 247: Applied Computational Analysis II by the Department of Electrical & Computer Engineering Technology at New York Institute of Technology Old Westbury. The LLM model is designed to be an instructive assistant, providing detailed explanations of concepts with examples from in-class notes without providing direct answers to questions. The model is designed with a RAG (Retrieval Augmented Generation) knowledge base and system prompt architecture. Examples in both code, text, and images are provided in the LLM responses.
Comments: 44 pages, 6 figures
Subjects:
Artificial Intelligence (cs.AI); Computers and Society (cs.CY)
Cite as: arXiv:2607.07846 [cs.AI]
(or arXiv:2607.07846v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2607.07846
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Ryan Duke [view email] [v1] Wed, 8 Jul 2026 18:27:39 UTC (4,584 KB)
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