AI Mathematical Olympiad Solver

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Authors: Nachiket Rakhonde, Rohan S. Sanap, Aarti Amod Agarkar, Rukmoddin Patel, Sanshodhan Soor
Cited by: 0

Abstract

This research presents AIMOS (AI- Powered Intelligent Math Operations System) — a multi- LLM orchestration framework to improve the correctness and reliability of mathematical problem- solving tasks. The framework annotates input questions to a category of mathematical discourse — Algebra, Calculus, Geometry, Trigonometry, or Probability & Statistics, then routes the questions to multiple large language model (LLM) APIs (including GPT-4, Claude, Gemini and Mistral) and levers their responses. The consensus algorithm and the trust-based algorithm follow to select the final response output with further symbolic verification of mathematical correctness. This experimental framework demonstrates that AIMOS outperforms use of single LLMs, with respect to correctness, reliability, and interpretability, and can be used for educational, research, and analytical purposes.

Fields of Study & Subjects

Intelligent Tutoring Systems and Adaptive Learning Mathematics Computing and Information Processing Artificial Intelligence in Education

Publication details

Journal / source
International Journal on Smart & Sustainable Intelligent Computing
Volume
2
Issue
4
Pages
24–33
Publication date
4 January 2026