---
title: "Who cites AI-Assisted Generation of Difficult Math Questions"
description: "22 papers of the Elamur Research library cite «AI-Assisted Generation of Difficult Math Questions», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/shah-2024-ai-assisted-generation-difficult-math/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [AI-Assisted Generation of Difficult Math Questions](https://md.research.elamur.ai/free/en/papers/shah-2024-ai-assisted-generation-difficult-math/) / cited by

# Who cites «AI-Assisted Generation of Difficult Math Questions»

22 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «AI-Assisted Generation of Difficult Math Questions»](https://md.research.elamur.ai/free/en/papers/shah-2024-ai-assisted-generation-difficult-math/)

1. [**MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations arXiv:2502.06453**Kaixuan Huang, Jiacheng Guo, Zihao Li, et al.*2025 · 42 citations*](https://md.research.elamur.ai/free/en/papers/huang-2025-math-perturb-benchmarking-llms-math/)
2. **[ATLAS: Autoformalizing Theorems through Lifting, Augmentation, and Synthesis of Data](https://md.research.elamur.ai/free/en/papers/liu-2025-atlas-autoformalizing-theorems-through-lifting/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoyang Liu, Kangjie Bao, Jiashuo Zhang, et al.*2025 · 16 citations*
3. [**MIND: Math Informed syNthetic Dialogues for Pretraining LLMs arXiv:2410.12881**Syeda Nahida Akter, Shrimai Prabhumoye, John Kamalu, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/akter-2024-mind-math-informed-synthetic-dialogues/)
4. [**Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation arXiv:2501.14275**Sadegh Mahdavi, Muchen Li, Kaiwen Liu, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/mahdavi-2025-leveraging-online-olympiad-level-math/)
5. **[AutoTaskEval: Towards Domain-Specific and Fine-Grained Evaluation for LLMs](https://md.research.elamur.ai/free/en/papers/lyu-2026-autotaskeval-domain-specific-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingqing Lyu, Linjuan Wu, Yongliang Shen, et al.*2026*
6. **[PuzzleClone: A DSL-Powered Framework for Synthesizing Verifiable Data](https://md.research.elamur.ai/free/en/papers/xiong-2026-puzzleclone-dsl-powered-framework-synthesizing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Xiong, Yanwei Huang, Rongjunchen Zhang, et al.*2026*
7. **[RV-Syn: Rational and Verifiable Mathematical Reasoning Data Synthesis based on Structured Function Library](https://md.research.elamur.ai/free/en/papers/wang-2026-rv-syn-rational-verifiable-mathematical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiapeng Wang, Jinhao Jiang, Zhiqiang Zhang, et al.*2026*

15 more papers of our library cite it; they have no page here yet.

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