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Kirito-Elucidator/MathModel-QA-Engine

2026 C 题 F 奖得主开发的数学建模/MCM/ICM O 奖论文 RAG 问答引擎:基于 LlamaIndex 章节级检索,支持年份/题号/章节过滤、建模方法/灵敏度分析/写作结构拆解,帮数模备赛快速复盘高分美赛论文

Why it is useful

MathModel-QA-Engine is a recent open-source project in Machine Learning. It is included because it has recent repository activity and can support mathematical learning, research, modelling, software development, or AI workflows.

Repository at a glance

  • Owner: Kirito-Elucidator
  • Primary language: Python
  • Latest update: 2026-09-20
  • Stars / forks: 11 / 0
  • License: MIT
  • Links: No separate project site was listed.

Good starting points

  1. Read the project README and installation instructions.
  2. Try the smallest example before changing parameters or datasets.
  3. Check tests, issues, and release notes before relying on results in teaching or research.
  4. Cite the repository and its license when reusing code or figures.

README snapshot

div align="center" 数学建模竞赛论文 RAG 问答引擎 基于 LlamaIndex 构建的检索增强生成(RAG)系统,专为分析 MCM/ICM (说不定还有国赛优化呢) 等数学建模竞赛历年获奖论文而设计。 h2🏆 MCM Finalist Award (F奖)/h2 /div --- ✨ 雄关漫道真如铁,而今迈步从头越 - 从起初的亚太,到不久前的 MathorCup - 从开始连论文排版都不会,到后来被逼成了全栈精通 - 从第一次打美赛拿到 S,到那天早上看到队友发来的 F 截图 感谢一直屡败屡战、反思调整的自己,也感谢一路以来共同进步、并肩作战的队友。🤝 旅程还没结束,还要复仇国赛!💪 --- p align="center" img src="assets/来时路1.jpg" alt="来时路 1" height="280" / img src="assets/来时路2.jpg" alt="来时路 2" height="280" / /p p align="center" img src="assets/架构图.png" alt="系统架构图" / /p 一切都启发于我在打美赛前准备阅读往年 O 奖论文时的苦痛,当时就联想到之前打别的比赛学习的 RAG 技