English

End-to-End Bangla AI for Solving Math Olympiad Problem Benchmark: Leveraging Large Language Model Using Integrated Approach

Computation and Language 2025-01-09 v1

Abstract

This work introduces systematic approach for enhancing large language models (LLMs) to address Bangla AI mathematical challenges. Through the assessment of diverse LLM configurations, fine-tuning with specific datasets, and the implementation of Retrieval-Augmented Generation (RAG), we enhanced the model's reasoning precision in a multilingual setting. Crucial discoveries indicate that customized prompting, dataset augmentation, and iterative reasoning improve the model's efficiency regarding Olympiad-level mathematical challenges.

Keywords

Cite

@article{arxiv.2501.04425,
  title  = {End-to-End Bangla AI for Solving Math Olympiad Problem Benchmark: Leveraging Large Language Model Using Integrated Approach},
  author = {H. M. Shadman Tabib and Jaber Ahmed Deedar},
  journal= {arXiv preprint arXiv:2501.04425},
  year   = {2025}
}
R2 v1 2026-06-28T20:59:43.701Z