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Open Access
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Divya K.K, Muhammed Dhanish K, Muhammed Rashid T, Muhammed Rishan O.K, Shabin Muneer,
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- Student, Department of Computer Science and Engineering,, Student, Department of Computer Science and Engineering,, Student, Department of Computer Science and Engineering,, Student, Department of Computer Science and Engineering,, Student, Department of Computer Science and Engineering, PA College of Engineering,, PA College of Engineering,, PA College of Engineering,, PA College of Engineering,, PA College of Engineering, Mangalore, Karnataka,, Mangalore, Karnataka,, Mangalore, Karnataka,, Mangalore, Karnataka,, Mangalore, Karnataka, India, India, India, India, India
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Abstract
nThe challenges of solving complex mathematical problems often hinder efficiency in various scientific and engineering domains. This project proposes an innovative solution to these challenges by integrating automated math solvers with large language model (LLM) retrieval-augmented generation (RAG). The proposed system aims to streamline mathematical problem-solving processes, offering a robust and precise tool for real-time recognition, classification, and solution generation. This work provides a novel method of automating the solution of mathematical problems by combining RAG (Retrieval-Augmented Generation) techniques with a Large Language Model (LLM). The suggested technique integrates outside information sources to improve accuracy and relevance while utilizing the advantages of LLMs to comprehend and provide answers for challenging mathematical problems. The system greatly enhances its capacity to handle a variety of mathematical topics, from fundamental arithmetic to advanced calculus, by accessing examples and contextual information from a curated database. By leveraging advanced algorithms and the computational power of LLMs, the system provides accurate and timely solutions to a wide array of mathematical problems. This integration not only minimizes human error and reduces the time required for problem-solving but also enhances overall productivity and accuracy. The automated math solver system with LLM RAG is poised to revolutionize the approach to mathematical problem-solving across various fields, ensuring increased reliability, efficiency, and innovation.
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Keywords: LLM, RAG, langchain, NLP, Mathematical problem
n[if 424 equals=”Regular Issue”][This article belongs to Journal of Electronic Design Technology(joedt)]
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References
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| Volume | 15 | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | 02 | |
| Received | June 18, 2024 | |
| Accepted | July 17, 2024 | |
| Published | August 17, 2024 |
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